Systems and/or methods for determining item serial number structure and intelligence

Information

  • Patent Grant
  • 9846871
  • Patent Number
    9,846,871
  • Date Filed
    Monday, March 24, 2014
    11 years ago
  • Date Issued
    Tuesday, December 19, 2017
    7 years ago
Abstract
Certain exemplary embodiments relate to techniques for determining the correct item serial number structure, even when information regarding the serial number data and/or structure is lacking. Such techniques advantageously promote data integrity by helping to ensure that the desired data is captured correctly, while also reducing (and sometimes even eliminating) the need to obtain detailed information regarding serial number structure and intelligence that sometimes is guarded by producers/manufacturers. Statistical sampling of collected unknown data formats may be used to help decipher product identification numbers (or other numbers) such as product serial numbers through a repetitive process of scanning a known constant such as the UPC number, followed by a variable number such as a products serial number. Certain exemplary embodiments check serial number against a database containing algorithms to determine if and which algorithm is used to create such serial numbers.
Description
TECHNICAL FIELD

Certain exemplary embodiments disclosed herein relate to techniques for efficiently handling the acquisition of serial number information from products at, for example, a point of sale (POS) system in a retail store. More particularly, certain exemplary embodiments disclosed herein relate to techniques for determining the correct item serial number structure, even when information regarding the serial number data and/or structure is lacking or even non-existent. Advantageously, the techniques of certain exemplary embodiments help ensure that the desired data is captured correctly, thereby promoting data integrity, while also reducing (and sometimes even eliminating) the need to obtain detailed information regarding serial number structure and intelligence that sometimes is guarded by producers/manufacturers.


BACKGROUND AND SUMMARY

Certain exemplary embodiments of this invention relate to the field of product serial numbers and their use in connection with an electronic registration system for such products. More particularly, certain exemplary embodiments provide techniques for efficiently handling the acquisition of serial number information from products at, for example, a point of sale (POS) system in a retail store or the like. In addition, certain exemplary embodiments also enable the correct item serial number structure to be determined. In certain exemplary instances, this determination may be made without the benefit of the producer/manufacturer of such items divulging the serial number data intelligence and/or structure.


Certain exemplary embodiments also are advantageous when used in connection with, for example, an electronic product registration system designed to be used with different products and/or different product manufacturers. Examples of electronic registration (ER) systems in which the instant invention may be used are described in the above-noted patent applications.


These electronic registration systems facilitate compliance with return policies and are useful in reducing improper or fraudulent product returns under warranty, and may also provide related functionality to third parties and the like. Such electronic registration systems also may enable real time or substantially real time data storage and retrieval for the purpose of verifying and validating sales transaction data and product return/warranty repair eligibility. These ER systems also enable efficient handling of product return transactions.


ER systems generally capture product serial number information at the time of product purchase. As a result, the POS system or register may be configured to scan or otherwise acquire the serial number information for purchased products for transmission to the ER system. It would be desirable for both ER and/or POS systems to verify the validity of serial numbers prior to storing them in the ER database, e.g., possibly prompting a clerk to rescan immediately so that potential errors or missing information could be identified prior to transmission to the ER system. The ability to collect and process a wide range of serial numbers without compromising the quality of the data collected is desirable when attempting to successfully implement an ER system. Typically, collection and implementation of serial numbers has required specific programming to ensure that the quality of the data collected is sound.


Thus, it will be appreciated that it would be desirable to develop generalized serial number handling capabilities that support implementation of a variety of serial number formats and also allow for an easy transition to allowing a single scan to identify a product and its serial number. Certain exemplary embodiments of this invention, for example, provide improved techniques for retrieving serial numbers for each Universal Product Code (UPC), which improves the efficiency and accuracy of ER systems and/or other systems in which such information is utilized.


Furthermore, certain exemplary embodiments may determine the correct item serial number structure, even when information regarding the serial number data and/or structure is lacking. Such techniques advantageously promote data integrity by helping to ensure that the desired data is captured correctly, while also reducing (and sometimes even eliminating) the need to obtain detailed information regarding serial number structure and intelligence that sometimes is guarded by producers/manufacturers.


Certain exemplary embodiments of this invention relate to techniques for deciphering product identification numbers (or other numbers) such as product serial numbers through a repetitive process of scanning a known constant such as the UPC number, followed by a variable number such as a product's serial number. Certain exemplary embodiments check serial number against a database containing algorithms to determine if and which algorithm is used to create such serial numbers. Such techniques may be useful for retailers, distributers, manufacturers, product return processing centers, reverse logistics operations, and/or like parties, where product serial number structure and intelligence may be unknown. Certain exemplary embodiments may also use statistical sampling of collected unknown data formats to help derive this and/or other data.


Programmed logic circuitry may include, for example, any suitable combination of hardware, software, firmware, and/or the like. A computer-readable storage medium may include, for example, a disk, CD-ROM, hard drive, and/or the like.


In certain exemplary embodiments, a method for determining a serial number structure when such information is missing or incomplete is provided. A non-transitory computer readable storage location stores at least one serial number mask, with each said serial number mask having an associated length. A serial number for a product is received, with the serial number having an associated length. If the length of the serial number does not equal the lengths of any existing masks stored in the non-transitory computer readable storage location as determined via at least one processor, a new serial number mask is created and the new serial number mask is stored to the non-transitory computer readable storage location via the at least one processor. If the length of the new serial number equals a length of an existing mask stored in the non-transitory computer readable storage location as determined via the at least one processor, the existing mask is altered as minimally as possible to allow the serial number to match the existing mask when the new serial number otherwise would not match the existing mask via the at least one processor. These steps may be repeated until a stable serial number mask is identified.


In certain exemplary embodiments, a method for determining a serial number structure when such information is missing or incomplete is provided. A UPC for a product is received. The UPC for the product is validated in connection with a check digit algorithm, a length validation routine, and/or a database of active UPCs, via at least one processor. A serial number for the product is received. The serial number is checked against the UPC to determine whether the serial number and UPC are the same via the at least one processor. A serial number mask is created for the serial number via the at least one processor. An attempt is made to locate a check digit or check digits within the serial number via the at least one processor. The serial number mask is stored to a storage location. The created serial number mask is iteratively refinable, until a stable serial mask pattern is detected, as further UPCs and further serial numbers are received for further products.


In certain exemplary embodiments, there are provided non-transitory computer readable storage mediums tangibly storing instructions that, when executed by at least one processor of a system, cause these and/or other methods to be executed.


In certain exemplary embodiments, a system for determining a serial number structure when such information is missing or incomplete. A first non-transitory computer readable storage medium comprises at least one known, predefined serial number mask, with each said serial number mask having an associated length. A second non-transitory computer readable storage medium comprises at least one known, predefined check digit algorithm. At least one processor is configured to: (a) receive a serial number for a scanned product, the serial number having an associated length, (b) create a new serial number mask and store the new serial number mask to the first non-transitory computer readable storage location if the length of the serial number does not equal the lengths of any existing masks stored in the first non-transitory computer readable storage location, (c) if the length of the new serial number equals a length of an existing mask stored in the non-transitory computer readable storage location, alter the existing mask as minimally as possible to allow the serial number to match the existing mask when the new serial number otherwise would not match the existing mask, and (d) cause (a)-(c) to be repeated until a stable serial number mask is identified.


The exemplary embodiments, aspect, and advantages described herein may be used in any suitable combination or sub-combination such that it is possible to obtain yet further embodiments of the instant invention.





BRIEF DESCRIPTION OF THE DRAWINGS

Aspects and characteristics of the exemplary illustrative non-limiting implementations will become apparent from the following detailed description of exemplary implementations, when read in view of the accompanying drawings, in which:



FIG. 1 is an exemplary product serial number and serial number mask;



FIG. 2 is a flowchart showing an illustrative process for determining a likely serial number mask in accordance with an exemplary embodiment;



FIG. 3 is a flowchart showing an illustrative processing loop to be used in connection with the FIG. 2 example process in accordance with an exemplary embodiment;



FIG. 4 is a simplified schematic view of an illustrative architecture for determining a likely serial number mask in accordance with an exemplary embodiment.





DETAILED DESCRIPTION

It will be recognized by those of ordinary skill that modification, extensions and changes to the disclosed exemplary implementations may be made without departing from the scope and spirit of the invention. In short, the present invention is not limited to the particular forms disclosed herein.


Certain exemplary embodiments may determine the correct item serial number structure, even when information regarding the serial number data and/or structure is lacking. Such techniques advantageously promote data integrity by helping to ensure that the desired data is captured correctly, while also reducing (and sometimes even eliminating) the need to obtain detailed information regarding serial number structure and intelligence that sometimes is guarded by producers/manufacturers. Such techniques may be useful for retailers, distributers, manufacturers, product return processing centers, reverse logistics operations, and/or like parties, where product serial number structure and intelligence may be unknown. Statistical sampling of collected unknown data formats may be used to help decipher product identification numbers (or other numbers) such as product serial numbers through a repetitive process of scanning a known constant such as the UPC number, followed by a variable number such as a products serial number. Certain exemplary embodiments check serial number against a database containing algorithms to determine if and which algorithm is used to create such serial numbers.


Generally, a serial number often comprises or consists of three parts: constants, alphanumeric variables, and zero or more check digits or characters. According to manufacturer preferences, the constants and check digit(s) are optional, and only the alphanumeric variables are required. The serial number constants, variables, and check digit(s) need not necessarily maintain positional integrity to be masked according to different implementations. Moreover, typically, serial numbers are not case sensitive. An example of a serial number 10 is shown in FIG. 1. The serial number 10 contains constants 12, alphanumeric variables 14, and a check digit 16. The total length of the serial number is eleven (11) digits.


The constants 12 are a part of the serial number that does not change from serial number to serial number. There may be multiple constants in any given serial number format. For instance, they may be a number, letter, or special character; they may be located in any portion of the serial number; and there may be more than one constant block. Generally, constants can be any value. In some instances, constants may represent special values such as product number, model number, or UPC.


Variables 14 are the portion of the serial number that varies from number to number. In some cases, the variables are alphanumeric, and there may be only one variable section within a serial number format, although multiple variable sections in a single serial number may be supported by the ER systems discussed above. Manufacturers may, however, define other serial number structures with one or more variable portions, and the one or more variable portions each may contain one or more alphanumeric characters. In this context, when multiple variable sections are defined in a serial number, one of the multiple sections can be defined as a primary variable that is used to perform additional checks within the ER system application, including setting a lowest serial number that is valid for registration.


The check digit 16 allows for additional validation when a serial number is captured. The check digit is calculated from one contiguous range of the serial number and may be a single number from 0 to 9, letter from A-Z, special character, etc. The check digit may be located after the range on which it was calculated, or in any suitable location within the serial number in certain structures. Check digit calculation may vary from serial number to serial number, and there are numerous possible ways to calculate a check digit or check digits.


With continued reference to FIG. 1, a serial number mask 20 generically defines attributes of a serial number format by including characters that characterize the serial number format. The generically defined attributes describe a serial number with uppercase and lowercase characters and numbers. Uppercase characters and numbers may describe constant values that have no special meaning in certain exemplary embodiments, whereas lowercase characters may describe variables, check digits, or have other special meanings.


Referring to the serial number 10 shown in FIG. 1, the mask 20 for the example serial number includes constants 22, defined as “NS” in positions 1 and 2, variables 24 defined as lowercase “x” in positions 3-10, and a check digit 26 defined as a lowercase “y” in position 11.


Because serial numbers are not case sensitive, the uppercase “NS” may represent any combinations of lowercase or uppercase “NS” in a serial number (e.g., “NS,” “ns,” “Ns,” or “nS”). In some cases, the constant section(s) of a serial number may represent some special meaning such as a UPC code for a product, a model number for the product, or a vendor specific code for the product. For example, the following constant identifiers may be used to identify these constants:

    • “a”—when the lower case “a” is used, it represents a constant portion of the serial number that will be the UPC or G10 code for a given product;
    • “b”—when the lower case “b” is used, it represents a constant portion of the serial number that is the model number for that product;
    • “c”—when the lower case “c” is used, it represents a constant portion of the serial number that is used to identify the product that is vendor specific (e.g., something other than a model or UPC number).


The use of format characters allows for additional processing against a serial number such as single scan product identification and serial number collection. As an example, consider the following UCC standard format. For a product with UCC 128 or GS1 128 standard barcode format (01)00004549663025(21)NS123456784, the mask for this could look like “(01)00004549663025(21)NSxxxxxxxxy.” To allow additional flexibility, however, the following mask could also be used to represent the product serial number format “(01)aaaaaaaaaaaaaa(21)NSxxxxxxxxy.” In this case, the “a” segment is used to split out the product identification portion of the serial number.


Variables 24 in the mask refer to a fixed length portion of the serial number that may vary in value. This variable portion of the serial number in combination with the constant 22 gives the serial number its uniqueness to a particular product. As shown, the mask character to identify variables is “x.” The variable portion of the serial number may be alphanumeric and ascend in value to cause a reduced number of registration value edits. It sometimes may be desirable to set a minimum registration value for product return processing, so that fraudulent returns may be minimized. For example, an older product having a serial number lower than the minimum registration value could be flagged by the system as invalid, thereby preventing product return.


The check digit section 26 of the serial number mask is described using a lower case “y.” As noted above, the check digit is a value that is calculated on at least a portion of the variable part of the serial number and possibly the entire serial number.


With respect to UPC and multiple mask definition, the UPC typically is used to identify a product at point of sale. The UPC, however, is not required in using masking. All that is required is that a product has some unique identifier to relate to a mask or masks. Although each product identifier sometimes will have only one mask, it is possible that a given product identifier may have more than one mask. This may be desirable when a product of the same UPC or product identifier has more than one serial number format. Edits using the mask may check for multiple mask definitions to ensure the validity of the serial number being collected. A special mask definition character, for example, such as “i”, may be used to maintain a high level of validity checking in special cases such as when engineering revision and/or color codes are built into serial numbers. The mask definition characters may be effective for validity checking (e.g., length of the particular portion of a serial number), while ignoring the contents of that section of the serial number.


Consider the following exemplary serial number: 17563164PR1302C121. The mask for this serial number could be “xxxxxxxxPR1302C121”. The last four digits of this number, however, in this example are the engineering code for this product and could change several times a year, requiring the definition of a mask for each unique engineering code. A different way to implement masking in this context may involve using the “i” definition character. In this context, the mask could be “xxxxxxxxPR1302iiii”. Thus, one mask may work for all serial numbers, even if the serial number changes according to a modified engineering code. In certain exemplary embodiments, engineering and/or other codes (e.g., batch number, OEM, etc.) may be marked and/or tracked on a per-product and/or per-serial number basis. This information may be further stored and/or processed, e.g., for reporting purposes back to a manufacturer, distributor, or other party.


Of course, it will be appreciated that other serial number formats and serial number masks are known and may be used in connection with different embodiments of this invention. In other words, the present invention is not limited to any particular serial number format or serial number mask.


As alluded to above, a model number may be located within a mask and, as such, certain exemplary embodiments may include techniques for capturing a model number. In certain exemplary embodiments, it is possible to associate sets of start and end points with masks, each to identify for specific information encoded into a serial number. For example, a manufacturer might produce a series of serial numbers for UPC 712345678904 that include a model number and engineering revision codes, and be presented as follows:

    • HG12345GH121192
    • HG12346GH121193
    • HG12347AA139855


A mask for this UPC might be: HGxxxxxzzxxxxx. In this example, the model may be encoded in positions 8 through 11. Furthermore, in this example, engineering revision codes might be in positions 12 through 15.


It will be appreciated that associating the model number to the mask, and therefore the UPC, advantageously enables another validity check to be preformed so as to help confirm that the UPC and model number match. This processing may also help revert a UPC to a correct value if a retail point of sale system provided an incorrect value to the ER system (e.g., as a result of a data processing error, data transmission error, improperly scanned item, etc.). In certain exemplary embodiments, engineering revision codes may be extracted and used for product reporting, as such numbers sometimes are useful in analyzing sales and returns trends. Engineering revision codes also may be used in serial number validation if, for example, the manufacturer associated specific engineering codes to UPCs, or associated specific engineering revision codes to specific ranges in the variable portion of the serial number (e.g., positions 3-7).


As alluded to above, retailers, distribution centers, and third party companies, etc., capture information at POS locations, for example. Such information may be obtained for any number of reasons including, for example, to track individual product inventory throughout all or part of the product's lifecycle, for product activation purposes, etc. Such information may include the product's UPC number or an equivalent thereto (e.g., JAN, EAN, Item Number, SKU, etc.) and item serial number or other unique derivative encoded number associated with the individual product. The latter unique number sometimes may be a combination of UPC, serial number and/or other information; a unique external product identifier (such as an RFID, etc.); a key associated with an internal device (e.g., an Integrated Circuit) built into the product (such as a television or other electronic product); etc.


Unfortunately, however, manufacturers often do not follow any standardized serial number formats when generating and applying serial number labels to their products. Most serial numbers among different brands vary in the number of characters, combination of alphanumeric or other special characters, and check-digit algorithms they may incorporate. To make certain the desired/correct information is captured and ensure data integrity, the producer/manufacture of such items currently must be consulted to determine the proper serial number structure and intelligence that it has incorporated in to its serial number and if an algorithm is utilized in determining a check-digit. Once the information is ascertained, a system can be programmed, hard-coded or incorporated in to a serial number mask (see, for example, U.S. Pat. No. 6,947,941), to scrutinize and ensure accuracy of the serial number data entered.


Obtaining this information from a manufacturer may not always be feasible or possible. Indeed, obtaining the information may be more complicated when the manufacturer is a third party OEM, where there is no relationship or a strained relationship with the manufacturer. In such cases, the assignee of the instant application has determined that manufacturers may not be forthcoming with such information. Further complications arise because a product occasionally may have serial numbers of varying formats due to separate serialization standards at different manufacturing facilities. As a result, there currently is a need in the art to reduce errors when capturing such information, even when detailed format information is unknown.


Certain exemplary embodiments of this invention provide techniques for deciphering identification numbers such as product serial numbers through a repetitive process of scanning a known constant such as the UPC number, followed by a variable number such as a products serial number. The technique produces a list of serial number masks for each distinct pattern that arises. This derived information may help provide for dynamic data validation, e.g., to determine the correct item serial number structure and intelligence—sometimes even without the benefit of the producer/manufacturer of such items divulging the serial number data intelligence and/or structure.


In this regard, FIG. 2 is a flowchart showing an illustrative process for determining a likely serial number mask in accordance with an exemplary embodiment. In step S201, a UPC (or the like) is obtained, e.g., by read, scanning, or otherwise providing a barcode or other tag. In step S203, the UPC is validated. For instance, the system may check and validate that a correct UPC was input using the standard UPC check digit algorithm, length validation, etc. Optionally, a known UPC database of active UPCs may be consulted as a part of this process. In step S205, an item serial number may be provided. The serial number may be checked in step S207 to ensure that it is not a UPC number using UPC validation techniques. Again, a UPC database of active UPCs may be consulted. In one or more steps not shown, a warning message may be produced if a match is found. However, some manufacturers may produce serial numbers that randomly conform to the UPC check digit algorithm, so it may be desirable to continue with the process even though a warning is raised. In step S207, optional cross-reference checks may be performed. For instance, in certain exemplary embodiments, the entered number may be checked against a table of known Model Numbers that correlate with the input UPC number, the entered number may be checked against a table of known retail item number (e.g., SKUs or Stock Keeping Units) that correlate with the input UPC number, etc.


In step S211, a serial number mask may be created that is as specific as possible (e.g., including all constants). See, for example, U.S. Pat. No. 6,947,941 for example details as to how to create a serial number mask. This may include checking each possible alphanumeric character in the scanned serial number with all supported or known, predefined check digit algorithms. Each alphanumeric digit in the input serial number may be checked as a serial number check digit. The range of digits used in the calculation may be the longest set of contiguous integers preceding the digit being validated. This process may proceed from left to right and, if more than one digit matches an algorithm, then the digit that has had the largest range of values used in its calculation may be kept whereas the rest may remain either alphanumeric constants or alphanumeric place holders in the mask. The process then proceeds to step S213, which is a process loop that helps to iteratively refine the mask. The step S213 process loop is described in greater detail in connection with FIG. 3.


Referring now more particularly to FIG. 3, another serial number is scanned in step S301. Similar to step S207, the serial number is checked to ensure that it is not a UPC number using UPC validation techniques optionally including, for example, consultation of a UPC database of active UPCs. In step S305, optional cross-reference checks may be performed. For instance, the entered number may be checked against a table of known Model Numbers that correlate with the input UPC number, the entered number may be checked against a table of known retail item number (e.g., SKUs) that correlate with the entered UPC number, etc.


The serial number length is compared to length(s) of the existing mask(s) in S307. If there is a match, a determination is made in step S309 as to whether the serial number matches the mask. If there is no match, then the mask is altered (e.g., as minimally as possible) to allow the current serial number to match in step S311. In certain exemplary embodiments, regardless of whether there is an alteration or not, a search for possible check digits in the serial number may be performed in step S313. This process may be similar to that described above in connection with step S211. In certain exemplary embodiments, the check digit search of step S313 may only be performed in cases where alterations are made to the mask (e.g., when the result of step S309 is “no” and an alteration is performed in step S311). It will be appreciated that step S313 may cause one or more prior check digits to become invalid. This may indicate, for example, that the serial number may not have a check digit at all.


If the length of the serial number is not the same as an existing mask (e.g., “no” in step S307), then a new mask may be created in step S315. This process of step S315 may be similar to the step S211 process, and the newly created mask may be added to the list of known masks.


In certain exemplary embodiments, a list of check digit ranges, modular-arithmetic values, and check digit place holders may be saved for each invalid possibility so that the alteration of the mask in step S311 may proceed more efficiently, e.g., without having to re-check check-digit algorithms that are not valid for previously scanned serial numbers. This approach is shown as step S317 in FIG. 3. Although the placement of step S317 is shown following the mask alteration in step S311 and after creation of a new mask in step S315, it will be appreciated that this step S317 may be provided elsewhere in the process. Differently stated, this process step (like many of the other process steps) may be moved, duplicated, and/or rendered optional in different exemplary embodiments of this invention. In certain exemplary embodiments, following step S315, the process may return to step S301.


In any event, the FIG. 3 loop may be repeated until a satisfactory and stable set of serial number masks have been detected/established, and certain decisive factors are found suggesting the serial number submitted is indeed a serial number. In that regard, if a stable mask is not found in step S319, the process may return to step S301 at the top of FIG. 3. If, however, a stable mask is found in step S319, the process may exit to step S215 in FIG. 2. In step S215, once a satisfactory and stable pattern is discovered, the list of serial masks may be marked for further review. They may then be utilized to validate and screen further serial number entries for this particular product UPC. A stable pattern may be identified, for example, once a predetermined number (e.g., 100, 1,000, 10,000, etc.) or percentage (e.g., 50+%, 80%, 90%, 95%, 99%, etc.) of serial numbers pass through the detection loop without requiring a change to a particular candidate mask for the product. In certain exemplary embodiments, the stable pattern may be flagged for possible manual review once a stable pattern is suspected, e.g., for possible certification of the mask. In certain exemplary embodiments, flagged patterns may be transmitted in real-time or in batch (e.g., at predetermined time intervals, upon a request, etc.) to appropriate personnel (e.g., at the ER system, the manufacturer, the retailer, etc.) for confirmation and/or compliance purposes.


It will be appreciated that this process may be performed in real-time (e.g., at a POS location, when products are scanned in a warehouse, when data is fed to an ER system, etc.), ahead of time (e.g., in a certification process, possibly in connection with a batch of information provided by a manufacturer, etc.), etc.


The table below shows an example of how the illustrative process shown in the FIGS. 2 and 3 flowcharts may be used to iteratively search for a mask. More particularly, serial numbers are entered, an initial mask is defined, and the initial mask is iteratively refined so that it is made more and more generic.

















Serial Number
Mask
Algorithm









NS123456784
NS123456784




NS123456777
NS1234567xy
03, 10, R, 3, O, N, 10, L



NS588456770
NSxxx4567xy
03, 10, R, 3, O, N, 10, L



NS442972316
NSxxxxxxxxy
03, 10, R, 3, O, N, 10, L



NS442972315
NSxxxxxxxxx
N/A










The following table provides one example check digital parameter legend, e.g., that may be used to interpret the algorithm column in the table provided above.













Field



Number
Field Definition







1
Start Position: This value defines the first position in the serial number to be used



in the check digit calculation. Applied after drop characters have been removed.



Value Range: 1 to 99.


2
End Position: This value defines the last position in the serial number to be used in



the check digit calculation. Applied after drop characters have been removed.



Value Range: 1 to 99


3
Directional Operator: This value defines the odd and even characters within a



serial number.



Value Range: R-L, R, L-R, L



R-L: Right-to-Left. Defines the last character of a serial number, excluding



the check digit to be odd.



R: Same as “R-L”. This value is used in the compressed algorithm.



L-R: Left-to-Right. Defines the first character of a serial number, excluding



the check digit to be odd.



L: Same as “L-R”. This value is used in the compressed algorithm.


4
Multiplier Value: This value will be multiplied against each value, either even or



odd, as defined by argument 5 in the algorithm, to come up with a sum that is used



in the modulo calculation.



Value Range: 0 to 9


5
Multiplier Identifier: This value identifies whether the odd or even characters in a



serial number will have the multiplier value applied.



Value Range: O, E



O: Specifies odd characters shall have the multiplier value applied.



E: Specifies even characters shall have the multiplier value applied.


6
Reduction Identifier: When multiplying the positional number by the multiplier



value, there are at least two ways that the calculation may be performed. First, the



sum may be calculated by adding the result of each position multiplied by the



multiplier value. Second, the sum may be calculated by adding the reduced result of



each position multiplied by the multiplier value. Values are “reduced to a single



digit”, as follows. If a positional value multiplied by the multiplier value is greater



than or equal to 10, then each digit is added together to form a new reduced value.



This step may be repeated once more if the previous result also formed a number



greater than or equal to 10.



Value Range: Y, N



Y: Specifies that reducing should take place.



N: Specifies that reducing should not take place.


7
Modulo Value: The sum of the positional values, including application of the



multiplier, is divided by this value, and the resulting remainder of that calculation is



then used in further calculations specified by the Check Digit Operator. This



remainder will be referred to as the “modulo calculation result.”



Note: This is an optional argument. The default value is 10.



Value Range: 1 to 99.


8
Check Digit Operator: This operator is used to identify the method of reducing the



modulo calculation result (if necessary) to produce the final check digit.



Note: This is an optional argument. The default value is ‘L’.



Valid Range: L, Z, S



L: If the Check Digit Operator is ‘L’ then the final check digit is the last



digit of the following calculation: (Modulo value - modulo calculation



result).



Z: If the Check Digit Operator is ‘Z’ and the result of the following



calculation: (Modulo value - modulo calculation result) is equal to the



Modulo Value, then the final check digit result is 0.



If the Check Digit Operator is ‘Z’ and the result of the following



calculation: (Modulo value - modulo calculation result) is NOT equal to



the Modulo Value, then the final check digit is the last digit of (Modulo



value - modulo calculation result).



S: If the Check Digit Operator is ‘S’ then the final check digit is the last



digit of the modulo calculation result.










FIG. 4 is a simplified schematic view of an illustrative architecture for determining a likely serial number mask in accordance with an exemplary embodiment. An input mechanism (e.g., barcode scanner, RFID reader, or the like) is connected to a computer terminal 403. The computer terminal 403 may be provided at a POS or other suitable location. The computer terminal 403 also may be able to setup a workspace 405 so as to at least temporarily store serial number, mask, and algorithm information (e.g., as shown in the table above), as it executes using a processor instructions stored on a tangible computer readable storage medium that correspond, for example, to the process steps described above and in connection with FIGS. 2-3. As alluded to above, a database of known or predefined masks 407 and a database of known algorithms 409 may be accessible by the computer terminal 403. These databases 407 and 409 may be stored at local or remote locations (e.g., a network location) accessible by the computer terminal 403. It will be appreciated that multiple terminals 403 may have access to the databases 407 and 409, e.g., over a network location. In any event, referring once again to FIG. 4, the terminal 403 also may have access to cross-check systems and/or databases 411. As before, these systems/databases may be accessible via a network connection.


Certain exemplary embodiments may be thought of as being global. This may mean that the ER database may function across disparate systems throughout all or substantially all of an item's or a product's lifecycle (e.g., from manufacture to shipment to sale to return, etc.). The various system components may be located around the world and the system may be said to be global in this sense, as well.


Although certain exemplary embodiments have been described as relating to serial numbers and serial number masks, it will be appreciated that other data structures may be used. Furthermore, although many serial numbers contain constants, a UPC, and check digit, other information may be stored in place of, or in addition to, such information. The techniques described herein may be used to derive these structures, as well. In addition, although certain example formats and example algorithms have been described herein, different exemplary embodiments may be made to function with different formats and different algorithms. It also will be appreciated that the exemplary embodiments described herein may be made to function with masks where some data is known and some data is unknown, e.g., where manufacturers or the like make certain information known while protecting other types of information. Furthermore, as noted above, the techniques described herein also may be used in connection with RFID tags. See, for example, U.S. application Ser. No. 10/983,337, the entire contents of which are hereby incorporated herein by reference.


Furthermore, although certain exemplary embodiments have been described in relation to serial numbers and serial number masks, the exemplary techniques described herein may be applied to other types of masks. In certain exemplary embodiments, it may be possible to distinguish between different kinds of masks (e.g., serial number masks, shipping or tracking code masks, UPCs, SKUs, etc.). In certain instances, it may be desirable to identify different masks to determine, for example, whether the wrong type of information has been scanned. An indication may be made available to a clerk at a POS location for immediate correction, stored and/or sent to a manufacturer/logistics provider/retailer/other party to indicate that further training is necessary or desirable, to suggest that packaging should be changed (e.g., to reduce perceived confusion and improve the quality of scans), etc. Such information may be stored in the ER database (e.g., when it is product-related data) or in another separate database in different embodiments of this invention (e.g., when it includes more personal information). Capturing data in this way may help to improve the overall integrity of the data captured, as improperly scanned codes may be received and rejected, and a replacement prompt may be generated, so as to help obtain better data in the first instance. The ability to help ensure that the right data is obtained at the right time may also in certain instances help reduce fraud related to the scanning of knowingly improper data that is used to falsely populate an ER, crime prevention, watchlist, or other database.


Although certain exemplary embodiments have been described as relating to POS systems, it will be appreciated that the exemplary embodiments may be implemented at other locations. For example, logistics provides, retailers, wholesalers, auction houses (online or conventional), pawnshops, and/or the like, also may find the techniques described herein useful. The same also holds true for law enforcement and/or other personnel. See, for example, U.S. application Ser. No. 12/314,150 for example details concerning law enforcement operations and U.S. application Ser. No. 11/892,415 for example details concerning auction houses and/or pawnshops. The entire contents of these applications are hereby incorporated herein by reference.


While the invention has been described in connection with exemplary illustrative non-limiting implementations, it is to be understood that the invention is not to be limited to the disclosed implementations, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims
  • 1. A method for determining a serial number structure when such information is missing or incomplete, the method comprising: receiving via an electronic communication from a point of sale (POS) terminal a universal product code (UPC) for a product;validating, via at least one processor, the UPC for the product in connection with a check digit algorithm, a length validation routine, and/or a database of active UPCs;receiving a serial number for the product;checking, via the at least one processor, the serial number against the UPC to determine whether the serial number and UPC are the same;creating, via the at least one processor, a serial number mask for the serial number;
  • 2. The method of claim 1, wherein the stable serial mask pattern is identified when a predetermined number or percentage of matches are made without requiring any changes to the corresponding mask.
  • 3. The method of claim 2, further comprising flagging the stable serial number mask for manual follow-up.
  • 4. The method of claim 1, wherein the searching is performed each time an existing mask is refined.
  • 5. The method of claim 1, further comprising handling the validating of the digit(s) from most significant digit to least significant digit and, if more than one digit or group of digits matches a run algorithm, then recording the digit or group of digits that has had the largest range of values used in its calculation as the check digit(s), and designating any remaining characters as either alphanumeric constants or alphanumeric place holders in the mask.
  • 6. The method of claim 1, wherein the validating of the UPC for the product is performed in connection with at least two of: a check digit algorithm, a length validation routine, and a database of active UPCs.
  • 7. The method of claim 1, wherein serial number and/or UPCs are receivable from a point-of-sale (POS) location.
  • 8. A system for determining a serial number structure when such information is missing or incomplete, the system comprising: at least one non-transitory computer readable storage medium tangibly storing at least one known, predefined serial number mask and a database of active universal product codes (UPCs); andat least one processor configured to: enable receipt of a UPC for a product;validate the UPC for the product in connection with a check digit algorithm, a length validation routine, and/or the database of active UPCs;enable receipt of a serial number for the product;check the serial number against the UPC to determine whether the serial number and UPC are the same;create a serial number mask for the serial number;
  • 9. The system of claim 8, wherein the at least one processor is configured to identify the stable serial mask pattern when a predetermined number or percentage of matches are made without requiring any changes to the corresponding mask.
  • 10. The system of claim 9, wherein the at least one processor is configured to flag the stable serial number mask for manual follow-up.
  • 11. The system of claim 10, wherein the at least one processor is configured to enable receipt of a human-provided indication as to whether the stable serial number mask should be accepted or rejected.
  • 12. The system of claim 8, wherein the at least one processor is configured to search for one or more possible check digits in the serial number each time an existing mask is refined.
  • 13. The system of claim 8, wherein the at least one processor is configured to handle the validating of the digit(s) from most significant digit to least significant digit and, if more than one digit or group of digits matches a run algorithm, record the digit or group of digits that has had the largest range of values used in its calculation as the check digit(s), and designate any remaining characters as either alphanumeric constants or alphanumeric place holders in the mask.
CROSS-REFERENCE TO RELATED APPLICATION

This application is a divisional of U.S. application Ser. No. 13/084,882 filed Apr. 12, 2011 which claims the benefit of U.S. Application Ser. No. 61/282,857, filed on Apr. 12, 2010, the entire contents of which are hereby incorporated by reference herein. This application also incorporates by reference the entire contents of U.S. Pat. Nos. 6,947,941; 6,085,172; 6,018,719; and 5,978,774.

US Referenced Citations (239)
Number Name Date Kind
789106 Seymour May 1905 A
1330368 Boos Feb 1920 A
1393489 Boos Oct 1921 A
1476819 Hope Dec 1923 A
4312037 Yamakita Jan 1982 A
4317957 Sendrow Mar 1982 A
4414467 Gould et al. Nov 1983 A
4458802 MacIver et al. Jul 1984 A
4563739 Gerpheide et al. Jan 1986 A
4598810 Shore et al. Jul 1986 A
4668150 Blumberg May 1987 A
4734005 Blumberg Mar 1988 A
4750119 Cohen Jun 1988 A
4789054 Shore et al. Dec 1988 A
4792018 Humble et al. Dec 1988 A
4803348 Lohrey Feb 1989 A
4812629 O'Neil et al. Mar 1989 A
4814592 Bradt Mar 1989 A
4839505 Bradt et al. Jun 1989 A
4858743 Paraskevakos et al. Aug 1989 A
4866661 De Prins Sep 1989 A
4871054 Murray Oct 1989 A
4884212 Stutsman Nov 1989 A
4893705 Brown Jan 1990 A
4896024 Morello et al. Jan 1990 A
4903815 Hirschfeld et al. Feb 1990 A
4967906 Morello et al. Nov 1990 A
4984155 Geier et al. Jan 1991 A
4997076 Hirschfeld Mar 1991 A
5007518 Crooks et al. Apr 1991 A
5020958 Tuttobene Jun 1991 A
5028766 Shah Jul 1991 A
5042686 Stucki Aug 1991 A
5057677 Bertagna Oct 1991 A
5128520 Rando et al. Jul 1992 A
5128527 Kawai et al. Jul 1992 A
5133441 Brown Jul 1992 A
5139384 Tuttobene Aug 1992 A
5143193 Geraci Sep 1992 A
5159560 Newell et al. Oct 1992 A
5216612 Cornett et al. Jun 1993 A
5231569 Myatt et al. Jul 1993 A
5256863 Ferguson Oct 1993 A
5257741 Rode et al. Nov 1993 A
5273183 Tuttobene Dec 1993 A
5311424 Mukherjee et al. May 1994 A
5367148 Storch et al. Nov 1994 A
5384449 Pierce Jan 1995 A
5414252 Shinoda et al. May 1995 A
5457307 Dumont Oct 1995 A
5478990 Montanari Dec 1995 A
5520990 Rotermund May 1996 A
5521815 Rose May 1996 A
5537314 Kanter Jul 1996 A
5541394 Kouchi et al. Jul 1996 A
5581064 Riley et al. Dec 1996 A
5602377 Beller et al. Feb 1997 A
5621201 Langhans Apr 1997 A
5671279 Elgamal Sep 1997 A
5712989 Johnson Jan 1998 A
5721832 Westrope et al. Feb 1998 A
5729693 Holda-Fleck Mar 1998 A
5737726 Cameron Apr 1998 A
5745036 Clare Apr 1998 A
5754981 Veeneman May 1998 A
5765143 Sheldon Jun 1998 A
5799285 Klingman Aug 1998 A
5804803 Cragun Sep 1998 A
5857175 Day Jan 1999 A
5878401 Joseph Mar 1999 A
5890138 Goidin Mar 1999 A
5895073 Moore Apr 1999 A
5895453 Cook Apr 1999 A
5913210 Call Jun 1999 A
5918214 Perkowski Jun 1999 A
5943424 Berger Aug 1999 A
5949335 Maynard Sep 1999 A
5950173 Perkowski Sep 1999 A
5961651 Gittins Oct 1999 A
5966450 Hosford Oct 1999 A
5968110 Westrope et al. Oct 1999 A
5984508 Hurley Nov 1999 A
6014635 Harris et al. Jan 2000 A
6016480 Houvenour Jan 2000 A
6029139 Cunningham et al. Feb 2000 A
6029141 Bezos et al. Feb 2000 A
6039244 Finstrewald Mar 2000 A
6049778 Walker Apr 2000 A
6055511 Luebbering et al. Apr 2000 A
6064979 Perkowski May 2000 A
6085167 Iguchi Jul 2000 A
6105001 Masi Aug 2000 A
6115690 Wong Sep 2000 A
6119099 Walker et al. Sep 2000 A
6119164 Basche Sep 2000 A
6125352 Franklin Sep 2000 A
6134533 Shell Oct 2000 A
6148249 Newman Nov 2000 A
6154738 Call Nov 2000 A
6169976 White Jan 2001 B1
6219652 Carter et al. Apr 2001 B1
6222914 McMullin Apr 2001 B1
6315199 Ito Nov 2001 B1
6317028 Vailius Nov 2001 B1
6334116 Ganesan Dec 2001 B1
6450407 Freeman Sep 2002 B1
6536659 Hauser Mar 2003 B1
6550685 Kindberg Apr 2003 B1
6591098 Sheih Jul 2003 B1
6592035 Mandile Jul 2003 B2
6606608 Bezos Aug 2003 B1
6609106 Robertson Aug 2003 B1
6612487 Tidball Sep 2003 B2
6622015 Himmel Sep 2003 B1
6633877 Saigh Oct 2003 B1
6697812 Martin Feb 2004 B1
6721332 McAlear Apr 2004 B1
6746053 Afzali-Ardakani et al. Jun 2004 B1
6748365 Quinlan Jun 2004 B1
6754637 Stenz Jun 2004 B1
6785537 Hicks Aug 2004 B2
6827260 Stoutenburg Dec 2004 B2
6834268 Junger Dec 2004 B2
6837426 Tidball Jan 2005 B2
6847935 Solomon Jan 2005 B1
6865544 Austin Mar 2005 B1
6933848 Stewart et al. Aug 2005 B1
6947941 Koon Sep 2005 B1
6965866 Klein Nov 2005 B2
6974941 Kuo Dec 2005 B2
7000834 Hind Feb 2006 B2
7003500 Driessen Feb 2006 B1
7035813 Cook Apr 2006 B1
7090138 Rettenmeyer Aug 2006 B2
7117227 Call Oct 2006 B2
7118478 Fayter et al. Oct 2006 B2
7124941 OConnell Oct 2006 B1
7143055 Perkowski Nov 2006 B1
7162440 Koons Jan 2007 B2
7191142 Sandell Mar 2007 B1
7249097 Hutchison Jul 2007 B2
7254124 Refai Aug 2007 B2
7281653 Beck Oct 2007 B2
7311249 Smith Dec 2007 B2
7343406 Buonanno Mar 2008 B1
7353178 Gorski Apr 2008 B2
7376572 Siegel May 2008 B2
7379899 Junger May 2008 B1
7415429 Rollins Aug 2008 B2
7415617 Ginter et al. Aug 2008 B2
7455230 Junger et al. Nov 2008 B2
7580860 Junger Aug 2009 B2
7660721 Williams Feb 2010 B2
7693731 Weber et al. Apr 2010 B1
7729923 O'Connor Jun 2010 B2
7760721 Stogel Jul 2010 B2
7797164 Junger et al. Sep 2010 B2
7840439 O'Connor Nov 2010 B2
7850081 Swan et al. Dec 2010 B2
7890373 Junger Feb 2011 B2
8036953 Hsu Oct 2011 B2
8190449 Grady May 2012 B2
8229861 Trandal Jul 2012 B1
8244644 Knipfer Aug 2012 B2
8260984 Iima Sep 2012 B2
8321302 Bauer Nov 2012 B2
8332323 Stals Dec 2012 B2
8442844 Trandal May 2013 B1
20020010627 Lerat Jan 2002 A1
20020022966 Horgan Feb 2002 A1
20020032612 Williams et al. Mar 2002 A1
20020091593 Fowler Jul 2002 A1
20020116274 Hind et al. Aug 2002 A1
20020133425 Pederson et al. Sep 2002 A1
20020143671 Afzali-Ardakani et al. Oct 2002 A1
20030004737 Conquest Jan 2003 A1
20030050891 Cohen Mar 2003 A1
20030083930 Burke May 2003 A1
20030094494 Blanford May 2003 A1
20030126034 Cheney et al. Jul 2003 A1
20030126079 Roberson Jul 2003 A1
20030141358 Hudson et al. Jul 2003 A1
20030144910 Flaherty Jul 2003 A1
20030149573 Lynton Aug 2003 A1
20030174823 Justice Sep 2003 A1
20030216969 Bauer Nov 2003 A1
20040006514 Rogers Jan 2004 A1
20040015418 Dooley Jan 2004 A1
20040037250 Refai Feb 2004 A1
20040054900 He Mar 2004 A1
20040088230 Elliott May 2004 A1
20040128395 Miyazaki Jul 2004 A1
20040153344 Bui et al. Aug 2004 A1
20040153402 Smith Aug 2004 A1
20040172260 Junger et al. Sep 2004 A1
20040195341 Lapstun et al. Oct 2004 A1
20040199760 Mazza et al. Oct 2004 A1
20040224660 Anderson Nov 2004 A1
20050049927 Zelanis Mar 2005 A1
20050097054 Dillon May 2005 A1
20050100144 O'Connor May 2005 A1
20050125292 Kassab Jun 2005 A1
20050137882 Cameron et al. Jun 2005 A1
20050149387 O'Shea Jul 2005 A1
20050240473 Ayers Oct 2005 A1
20060058011 Vanska Mar 2006 A1
20060129456 Walker Jun 2006 A1
20060136299 Ruhmkorf Jun 2006 A1
20060175401 Roberts Aug 2006 A1
20060190337 Ayers Aug 2006 A1
20070100761 Dillon May 2007 A1
20070143177 Graves Jun 2007 A1
20070185788 Dillon Aug 2007 A1
20080008348 Metois Jan 2008 A1
20080052184 Junger et al. Feb 2008 A1
20080059226 Melker Mar 2008 A1
20080089686 Kazawa et al. Apr 2008 A1
20080179390 Harjani Jul 2008 A1
20080186174 Alexis Aug 2008 A1
20080188974 Knipfer et al. Aug 2008 A1
20080256600 Schrijen Oct 2008 A1
20080262948 Grady Oct 2008 A1
20080317469 Kazawa et al. Dec 2008 A1
20090048934 Haddad Feb 2009 A1
20090076870 Hammond Mar 2009 A1
20090150170 Junger et al. Jun 2009 A1
20090240516 Palestrant Sep 2009 A1
20090281935 Junger Nov 2009 A1
20090319352 Boyle Dec 2009 A1
20100095357 Willis Apr 2010 A1
20100185533 O'Connor Jul 2010 A1
20100235290 Junger et al. Sep 2010 A1
20100257486 Smith Oct 2010 A1
20100325020 Junger et al. Dec 2010 A1
20110016008 Maraz et al. Jan 2011 A1
20110029397 Junger Feb 2011 A1
20110066514 Maraz Mar 2011 A1
20110251911 Junger et al. Oct 2011 A1
20120313754 Bona Dec 2012 A1
Foreign Referenced Citations (80)
Number Date Country
PI 9813567-8 Oct 2000 BR
0101819-1 Feb 2003 BR
PI 0503016-1 Oct 2005 BR
PI 0505846-5 Sep 2007 BR
2374623 Apr 2001 CA
2404814 Oct 2001 CA
2408553 Nov 2001 CA
1177408 Mar 1998 CN
1289972 Apr 2001 CN
101068731 Nov 2007 CN
101089871 Dec 2007 CN
3 315 724 Oct 1984 DE
0 068 642 Jan 1983 EP
0 191 636 Aug 1986 EP
0 286 130 Oct 1988 EP
0 349 284 Jan 1990 EP
0 845 749 Jun 1998 EP
0 862 154 Sep 1998 EP
1 028 386 Aug 2000 EP
1 841 195 Nov 2000 EP
1 195 704 Apr 2002 EP
1 246 109 Oct 2002 EP
1 571 541 Mar 2005 EP
1 667 018 Oct 2005 EP
2 036 015 Dec 2007 EP
2 559 599 Aug 1985 FR
2 143 662 Feb 1985 GB
2 203 879 Oct 1988 GB
2 209 157 May 1989 GB
2 209 158 May 1989 GB
200000127 Oct 2000 GT
200000061 Nov 2000 GT
200300100 Mar 2006 GT
200200141 Jul 2007 GT
1072CHENP2003 Jul 2005 IN
1763CHENP2003 Mar 2007 IN
2137CHENP2005 Jul 2007 IN
538MUM2008 Apr 2008 IN
8258DELNP2007 Apr 2008 IN
8266DELNP2007 Jul 2008 IN
303KOLNP2008 Dec 2008 IN
53KOL2008 Apr 2009 IN
1421KOLNP2009 Jun 2009 IN
2-139698 May 1990 JP
04-347793 Dec 1992 JP
05-178422 Jul 1993 JP
05-342482 Dec 1993 JP
08-124033 May 1996 JP
10-188141 Jul 1998 JP
10-340301 Dec 1998 JP
11-066176 Mar 1999 JP
11-143954 May 1999 JP
2000-123078 Apr 2000 JP
2002-279090 Sep 2002 JP
2002-133080 Oct 2002 JP
2003-316871 Nov 2003 JP
2005-141374 Jun 2005 JP
2005-234981 Sep 2005 JP
2007-226516 Sep 2007 JP
2007-257561 Oct 2007 JP
2008-197768 Aug 2008 JP
2009-032171 Feb 2009 JP
218248 Mar 1998 MX
PAA2000002497 Mar 1999 MX
221246 Jul 1999 MX
PAA2002000636 Nov 2001 MX
MXA2007014520 Nov 2006 MX
1991000023 Jan 1991 SV
1996000019 Jan 1996 SV
1998000129 Jan 1998 SV
2000000045 Jan 2000 SV
2000000145 Jan 2000 SV
2003001513 Jan 2003 SV
2003001514 Jan 2003 SV
8700948 Feb 1987 WO
8802524 Apr 1988 WO
8806771 Sep 1988 WO
8909460 Oct 1989 WO
9201273 Jan 1992 WO
9933016 Jul 1999 WO
Non-Patent Literature Citations (86)
Entry
1992 Nintendo Product Returns Policy.
1994 Nintendo Product Returns Policies and Procedures.
1995 Nintendo Product Returns Policies and Procedures.
1996 Nintendo Product Returns Policies and Procedures.
Jan. 6, 2005 Blog (Message 4 of 17) about Schuman article “Bar-Code Scam at Wal-Mart: A Matter of Priorities”.
Jan. 13, 2005 Blog (Message 14 of 17) about Schuman article “Bar-Code Scam at Wal-Mart: A Matter of Priorities”.
Amazon.com Returns Policy, printed Dec. 14, 2007, 2 pages.
Automatic I.D. News, No more scamming Super Mario, vol. 12, p. 15 (1 pg.), Sep. 1, 1996.
Automotive News, “Reynolds, ADP differ on superhighway progress”, Crain Communications, Inc., Apr. 11, 1994, 3 pages.
Birnbaum, Henry, General Information Manual: IBM Circulation Control at Brooklyn College Library, 29pp. (ON 001822-ON 001850).
Brewin et al., “Follow That Package!”, Computer World, vol. 35, No. 12, Mar. 19, 2001, 4 pages.
Business Wire, “Aztech Labs Inc. is Chosen as Business Depot's Vendor of the Year; Canadian Company Honors Multimedia Hardware Manufacturer as Number One in Computer Category”, Business Wire, Inc., May 6, 1996, 2 pages.
Business Wire, “DataTrend receives award from AT&T Global Information Solutions”, Business Wire, Inc., Nov. 7, 1995, 2 pages.
Business Wire, “Multimillion-dollar Health-care Products”, Business Wire, Inc., Dec. 15, 1993, 2 pages.
Canadian Search Report for Application No. 2,350,551 dated Jan. 21, 2004.
CollegeTermPapers web page printout, “History of Fed Ex”, www.collegetermpaper...rmPapers/Aviation/history—of—fed—ex.html (Aug. 24, 2001), 7 pages.
Collins, David Jarrett and Nancy Nasuti Whipple, Using Bar Code: Why It's Taking Over, Second Edition (ON 003696-ON 004031).
Computer Reseller News, “Case Study; Tapping the Channel's ‘Best in Class’”, CMP Publications, Inc., Jan. 30, 1995, 2 pages.
Consumer Electronics, Warren Publishing, Inc., Consumer Electronics Personals, vol. 35, No. 6, p. 18.
Cooper, Michael D., Design of Library Automation Systems, pp. 83-109 (ON 1859-ON 001873).
Corbin, John, Developing Computer-Based Library Systems, pp. 144-149 (ON 001874-ON 001877).
DataPhase, Inc. Automated Circulation System, 43 pp. (ON 001878-ON 001904).
Deposition of Peter J. Junger, vol. 1 & 2 (Nov. 8-9, 2001) and Exhibits 1-4 & 8-19.
Deposition of Philip M. Rogers (Nov. 7, 2001) and Exhibits 1-19.
Dilger, “The Other Direction”, Manufacturing Systems, vol. 15, No. 10, pp. 12-13 (Oct. 1997).
Direct Return 2000, Software Overview, http://www.directreturn.com/software—overview.htm, Copyright © 2000 Pharmacy Software Solutions, Inc.
Discount Store News, “New Policy System can Par Suspect Returns, Cut Losses”, Discount Store News, Lebhar-Friedman Inc., Jan. 1, 1996, 2 page.
Dowlin, Kenneth E., “MAGGIE III: The Prototypical Library System”, Library Hi Tech, Issue 16, vol. 4, No. 4, Winter 1986, pp. 7-15 (ON 001960-ON 001970).
Dranov, Paula, Automated Library Circulation Systems, 1977-78, pp. 24-47 (ON 001905-ON 001929).
Dreamcom web page printout, www.dreamcomdirect.com/RMA.htm (May 25, 1997).
Drug Topics, Software Maker Promises Many Happy Returns, pp. 124 & 128, Mar. 4, 1996.
Emigh, Jacqueline, “Item-Level RFID is Years Away for Retailers”, eWeek, Jan. 5, 2005.
Federal Express Information Packet, 56 pages. (incl. cover and table of contents).
Fox Appliance Return Parts Policy, Aug. 5, 2003, www.foxmacon.com, online, pp. 1-3.
Georgianis, Computer City Moves to Consolidate Returns, Computer Retail Systems, vol. 6, No. 125, Jan. 22, 1998, 2 pages.
Grace, “ABCD Looks to Adopt EDI Transaction Sets”, Computer Reseller News, CMP Publications, Inc., Jun. 28, 1993, 2 pages.
Grace, “Reseller Profile—Reynolds and Reynolds; Reynolds goes extra mile—Evolving solutions continue to fuel clients' capabilities”, Computer Reseller News, CMP Publications, Inc., Feb. 21, 1994, 2 pages.
Grosch, Audrey N., Distributed Computing and the Electronic Library: Micros to Superminis, pp. 78-79 (ON 002144-ON 002146).
Grotta, “Return to vendor: the right way to make mail-order returns”, PC Sources, Information Access Company, a Thomson Corporation Company, ASAP Coastal Associates Publishing L.P., Feb. 1992, 10 pages.
Heller, “High cost of returns prompts industry cooperation,” Discount Store News, Oct. 1998, 3 pages.
Hoadley, Irene Braden and A. Robert Thorson, An Automated On-Line Circulation System: Evaluation, Development, Use, 1973, 19 pp. (ON 001930-ON 001948).
Hughes Network Systems, LLC, “HughesNet Terms & Conditions”, http://www.nationwidesatellite.com/HughesNet/service/HughesNet—terms.asp, available online Sep. 2, 2008.
IBM Systems Journal, vol. 14, No. 1, 1975, pp. 1-101.
Information Disclosure Statement filed in U.S. Appl. No. 08/725,259 on Oct. 5, 1998.
Information Disclosure Statement filed in U.S. Appl. No. 09/065,552 on Jul. 19, 1999.
Information Disclosure Statement filed in U.S. Appl. No. 09/362,187 on Oct. 26, 2001.
Information Disclosure Statement filed in U.S. Appl. No. 09/494,540 on Jan. 31, 2000.
Information Disclosure Statement filed in U.S. Appl. No. 09/509,021 on Oct. 26, 2001.
Information Disclosure Statement filed in U.S. Appl. No. 09/809,072 on Oct. 26, 2001.
Jiji Press Ticker Service, “JCCI Issues Booklet to Explain Distribution”, Jiji Press Ltd., Jul. 20, 1989, 1 page.
Jiji Press Ticker Service, “MITI Working Out Business Practice Guidelines”, Jiji Press Ltd., Apr. 20, 1990, 1 page.
Joachim, “FedEx Delivers on CEO's IT Vision”, InternetWeek, Oct. 25, 1999, 4 pages.
LaPlante, “Rugby Darby; From proprietary host to a distributed LAN-based architecture in 2 years”, InfoWorld, InfoWorld Media Group, Nov. 15, 1993, 4 pages.
Leyden, “Burgled mum finds stolen iPod on eBay,” The Register, May 17, 2005, 1 page.
Longwell, “Robec Links Its 18 Sales Facilities Via Newly Adopted NetWare System”, Computer Reseller News, Sep. 6, 1993.
Longwell, “Western Digital Wins—Price/performance gives driver maker victory margin”, Computer Reseller News, CMP Publications, Inc., Jun. 28, 1993, 3 pages.
“Man accused in Lego selling scam,” http://www.kptv.com/Global/story.asp?S=4137050&nav=munil56—2, Nov. 18, 2005, 1 page.
Margulis, “Reclaim: an efficient way to handle damaged products”, U.S. Distribution Journal, BMT Publications Inc., Mar. 15, 1992, 7 pages.
Matthews, Joseph R., “Graphical User Interfaces GUI in Library Products”, Library Technology Reports, vol. 32, No. 1, Jan. 1996, p. 53 (ON 001972-ON 001976).
Meyer, James, “NOTIS: The System and Its Features”, Library Hi Tech, Issue 10, vol. 3, No. 2, 1985, pp. 81-89 (ON 001949-ON 001959).
Narda News, “Retailing in Cyberspace”, Apr. 1995, pp. 21-22.
Nintendo Point of Purchase Mail-In Card.
PR Newswire, “CompuServe Introduces Electronic Product Registration Software”, PR Newswire Association, Inc., Mar. 10, 1994, 2 pages.
PR Newswire, “Escada Offers a Garden Variety for Spring”, PR Newswire Association, Inc., Mar. 10, 1994, 2 pages.
Quinn, “Why Wang took the third-party route”, Information Access Company, a Thomson Corporation Company, ASAP Reed Publishing USA, vol. 30, No. 2, p. 30, Feb. 1991.
Reynolds, Dennis, Library Automation: Issues and Applications, pp. 42-49 and pp. 146-149 (ON 002147-ON 002153).
Rigney, “User Migrates to Windows NT”, InternetWeek, CMP Publications, Inc., Jan. 10, 1994, 2 pages.
Rogers et al., “Going Backwards: Reverse Logistics Trends and Practices”, Reverse Logistics Executive Council, 1998 (entire book).
Rosenbloom, “Midnight Express”, Inc., Jul. 2001, 4 pages.
Saffady, William, “Integrated Library Systems for Microcomputers and Mainframes: A Vendor Study”, Library Technology Reports, vol. 30, No. 1, Jan. 1994, p. 5 (ON 001977-ON 002087).
Saffady, William, “Vendors of Integrated Library Systems for Minicomputers and Mainframes: An Industry Report, part 1”, Library Technology Reports, vol. 33, No. 2, Mar. 1997, p. 161 (ON 002088-ON 002096).
Saffady, William, “Vendors of Integrated Library Systems for Microcomputers and Mainframes: An Industry Report, part 2”, Library Technology Reports, vol. 33, No. 3, May 1997, p. 277 (ON 002097-ON 002138).
Salmon, Stephen R., Library Automation Systems, p. 239 (ON 002154-ON 002155).
Salton, Gerard, Dynamic Information and Library Processing, pp. 62-69 (ON 002139-ON 002143).
Scala, Betsy Video Business, “Distributors seek 30-day returns”, v 13 , n 3 , p. I + Jan. 22, 1993.
Scala, Betsy Video Business, “Distributors seek 30-day returns”, v 15 , n. 39 , p. I + Oct. 6, 1995.
Schuman, Evan, “Bar-Code Scam at Wal-Mart: A Matter of Priorities”, eWeek, Jan. 5, 2005.
Schuman, Evan, “Wal-Mart Stung in $1.5 Million Bar-Code Scam”, eWeek, Jan. 5, 2005.
Sigafoos et al., “Absolutely Positively Overnight!: The Unofficial Corporate History of Federal Express”, St. Luke Press, 1988, pp. 1-22.
Sleeper, “FedEx Pushes the Right Buttons to Remain No. 1 in Fast Shipping”, Investors Business Daily, May 25, 2001, 2 pages.
Synchronics Software Product Information guide, 95 pages.
Synchronics® User Manual: Inventory Plus, Version 6.5, Apr. 1993 (ON 005117-ON 005892).
Synchronics® User Manual: Point of Sale, Version 6.5, Apr. 1993 (ON 004464-ON 005116).
White, Howard S., Library Technology Reports, Mar.-Apr. 1982, vol. 18,No. 2, pp. 178-184 (ON 001851-ON 001858).
Witt et al., “Distribution: a differentiator in 2000”, Material Handling Engineering, Penton Publishing Inc., Oct. 1995, 15 pages.
Witt, “How to Master the Art of Returns: Automation Is the Key”, Material Handling Engineering, Jun. 1994, pp. 58-60.
Related Publications (1)
Number Date Country
20140207599 A1 Jul 2014 US
Provisional Applications (1)
Number Date Country
61282857 Apr 2010 US
Divisions (1)
Number Date Country
Parent 13084882 Apr 2011 US
Child 14223238 US