Patent Application
20120257741
Telecommunications service providers often maintain a large inventory of telephone numbers available for assignment to end users. As part of the telephone service ordering system, telephone subscribers may be presented with available telephone numbers from which to choose. Various methodologies may be used for generating a sampling, from the vast inventory, of prospective telephone numbers that can practicably be presented to the subscriber for selection. With respect to 10-digit telephone numbers, the subscriber's location, for example, may prescribe the options available regarding the Numbering Plan “area code” (1st three digits) and/or the Central Office “exchange code” (next three digits).
The ordering system may then use some process by which to determine a limited set of “subscriber numbers” (last four digits) that is to be presented to the subscriber for selection. In practice, however, such winnowing processes typically do not account for the relative desirability of the telephone numbers themselves, from the perspective of subscribers in general and/or the immediate subscriber in particular.
The following detailed description refers to the accompanying drawings. The same reference numbers in different drawings may identify the same or similar elements. Also, the following detailed description does not limit the invention.
Implementations described herein relate to devices, methods, and/or systems that may be configured to determine quality indicators for telephone numbers, for example, based on mnemonic attributes that are determined using telephone keypad letter mapping. In some implementations, identified words and/or acronyms (“terms”), for letter sequences corresponding to the digits of the telephone numbers, may be scored to determine the respective quality indicators. In some implementations, recognized terms may be defined in a configurable list.
In general, scoring metrics may use one or more objective and/or subjective criteria, such as, term length, the number of terms, term location, term relevance/obscurity, for example, independently and/or in any combination, weighted and/or un-weighted, etc.
Once determined, the quality indicators may be used for facilitating management of telephone number inventory. In some implementations, the quality indicators may be compared to a threshold value for the purpose of conserving storage space in a database storing the terms in association with respective telephone numbers. In other implementations, the quality indicators may be used in searching a database of available telephone numbers. In still other implementations, the quality indicators may be used in establishing a fee schedule for assignment of different ones of the available telephone numbers.
Telecom system 110 may include one or more server entities, or other types of computation or communication devices, that gather, process, search, and/or provide information in a manner described herein. In one implementation, telecom system 110 may include a server (e.g., a computer system or an application), a workstation, and/or a service provider capable of providing telecommunication products and/or services. In some implementations, telecom system 110 may be configured to communicate with user device 120 and/or other device (not shown) in the manner described below.
User device 120 may include a radiotelephone, a personal communications system (PCS) terminal (e.g., that may combine a cellular radiotelephone with data processing and data communications capabilities), a personal digital assistant (PDA) (e.g., that can include a radiotelephone, a pager, Internet/intranet access, etc.), a laptop or notebook computer, a personal computer, an ultra mobile personal computer (UMPC), a netbook, or other types of computation or communication devices, threads or processes running on such devices, and/or objects executable by such devices. In one implementation, user device 120 may include any device (e.g., an Internet Protocol (IP)-based device) that is capable of accessing telecom system 110 via network 130.
Network 130 may include a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network, such as the Public Switched Telephone Network (PSTN), an intranet, the Internet, an optical fiber (or fiber optic)-based network, or a combination of networks.
Processing logic 220 may include a processor, microprocessor, or other type of processing logic that may interpret and execute instructions. Main memory 230 may include a random access memory (RAM) or another type of dynamic storage device that may store information and instructions for execution by processing logic 220. ROM 240 may include a ROM device or another type of static storage device that may store static information and/or instructions for use by processing logic 220. Storage device 250 may include a magnetic and/or optical recording medium and its corresponding drive.
Input device 260 may include a mechanism that permits an operator to input information to device 200, such as a keyboard, a mouse, a pen, a microphone, voice recognition and/or biometric mechanisms, into telecom system 110 and/or user device 120. Output device 270 may include a mechanism that outputs information to the operator, including a display, a printer, a speaker, etc. Communication interface 280 may include any transceiver-like mechanism that enables device 200 to communicate with other devices and/or systems. For example, communication interface 280 may include mechanisms for communicating with another device or system via a network, such as network 130.
As described herein, device 200 may perform certain operations in response to processing logic 220 executing software instructions contained in a computer-readable medium, such as main memory 230. A computer-readable medium may be defined as a physical or logical memory device. The software instructions may be read into main memory 230 from another computer-readable medium, such as storage device 250, or from another device via communication interface 280. The software instructions contained in main memory 230 may cause processing logic 220 to perform processes described herein. Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware devices, circuitry, and/or software.
Although
Parameter configuration logic 300 may include logic for setting various configuration or initialization data or parameters. In one implementation, parameter configuration logic 300 may be configured to receive user or operator input, via input device 260 and/or communication interface 280, for example, before and/or at any point during processing, providing one or more parameters for system processing, term list generation, such as letter mapping, term identification, term matching, term scoring, threshold determination, database searching, etc., as described in further detail below. Parameter configuration logic 300 may be configured to provide one or more default settings without user input for select parameters.
Term list generation logic 310 may include logic for creating a list of letter and/or numeric sequences to be recognized as “terms.” As used herein, term is intended to be broadly interpreted herein to include, for example, alphabetic and/or alphanumeric sequences of at least two characters (e.g. letters), forming a word, an acronym, an abbreviation (e.g. short message service/texting language), a phrase, a proper noun, etc. Terms may include implied hyphenation, spacing, phonetic and/or alternate spellings, supplied or appended trailing letters, contractions (e.g., implied apostrophes), numerals (e.g., 2, 4, 8, etc.), slang, jargon, and/or any other grammatical variants. In one implementation, term list generation logic 310 may be configured to reference dictionaries and other sources of word lists.
Term list generation logic 310 may generate and/or modify a particular term list based on user-specific information received, for example, from parameter configuration logic 300. In some implementations, term list generation logic 310 may maintain multiple term lists that differ. Term list generation logic 310 may be configured to exclude particular groups of words (e.g., profanity, potentially offensive, etc.) from the list of terms. Consistent with implementations described herein, term list generation logic 310 may be configured to set a minimum length (e.g., 2 characters) and a maximum length (e.g., 10 characters) for terms, based on information received from parameter configuration logic 300. The term list(s) may be stored in a database, for example, in main memory 230 and/or storage device 250.
Letter mapping logic 320 may include logic for converting digits of telephone numbers into a series of alphabet strings using conventional telephone keypad letter mapping, such as, 1=none; 2=A, B, C; 3=D, E, F; 4=G, H, I; 5=J, K, L; 6=M, N, O; 7=P, Q, R, S; 8=T, U, V; 9=W, X, Y, Z; and 0=none. Based on information received from parameter configuration logic 300, for example, the digit-to-letter mapping may be configured in any manner, for example, designating the digit “0” as the letter “O” and the digit “1” as the letter “l,” etc. Letter mapping logic 320 may be configured to generate a partial or an entire series of alphabet strings for a given telephone number. Consistent with embodiments described herein, letter mapping logic 320 may be configured to retain some digits that sound like words (e.g., 2, 4, 8, etc.) as numerals, to generate alphanumeric strings. Letter mapping logic 320 may be configured to adjust the letter mapping used based on user-specific information provided, for example, from parameter configuration logic 310, and/or select or modify a particular letter mapping system based on the user-specific information.
Term identification/matching logic 330 may include logic for identifying terms formed in the alphabet and/or alphanumeric strings provided from letter mapping logic 320 based on a comparison to the list(s) of terms provided from term list generation logic 310. For example, term identification/matching logic 330 may be configured to compare letter sequences (e.g., minimum of 2 letters) contained in the alphabet string to recognized terms. For matching purposes, term identification/matching logic 330 may be configured to treat some numerals (e.g., 2, 4, 8) as words (“to,” “too,”, “for,” “ate,” etc.). In another implementation, term identification/matching logic 330 may provide trailing letters to “complete” a term (that is, create a string that is longer than the telephone number), for example, in dialing plans/systems in which the extra numbers, if dialed, will be ignored. In some implementations, term identification/matching logic 330 and/or letter mapping logic may be configured to re-convert unmatched letters contained in the alphabet strings (and/or alphanumeric strings) back into numerals to create alphanumeric strings. Term identification/matching logic 340 may be configured to identify and/or match particular terms based on user-specific information provided, for example, from parameter configuration logic 310.
Scoring logic 340 may include logic scoring the alphabet strings (and/or alphanumeric strings) based on, for example, information received from term identification/matching logic 330. For example, scoring logic 340 may use one or more scoring metric to score the terms and/or combination of terms identified in the alphabet strings (and/or alphanumeric strings). Consistent with embodiments described herein, information received from parameter configuration logic 300 may be used to select or configure the one or more scoring metrics. In some embodiments, when multiple scoring metrics are used, scoring logic 340 may determine intermediary scores and then a final score based on the intermediary scores. Scoring logic 340 may be configured to adjust scores based on user-specific information provided, for example, from parameter configuration logic 310, and/or select or modify a particular scoring metric based on the user-specific information.
Threshold determination logic 350 may include logic for determining, based on information provided from parameter configuration logic 300, for example, a threshold value for comparing to scores provided from scoring logic 340. Threshold determination logic 350 may be configured to adjust threshold values based on user-specific information provided, for example, from parameter configuration logic 310, and/or select or modify a particular threshold value based on the user-specific information. Consistent with embodiments described herein, results of the comparison of the scores to the threshold value may be used to determine which of the alphabet strings (and/or alphanumeric strings) are and are not to be stored in association with the corresponding telephone numbers. In some embodiments, the results may be used to establish a fee schedule related to assignment of a particular telephone number, for example, as a one-time fee or on a recurring basis, indicative of a relative mnemonic value associated the telephone number.
Storing/search logic 360 may include logic for searching a telephone number inventory based on information, for example, provided from parameter configuration logic 300, term identification/matching logic 330 and/or threshold determination logic 350. Storing/search logic 360 may be configured to adjust searches based on queries and/or user-specific information provided, for example, from parameter configuration logic 310, and/or select or modify a particular search based on the queries and/or user-specific information. In one embodiment, search logic may search for a telephone number(s) that includes a particular search term identified in a query.
Next, a particular telephone number or set of telephone numbers are identified for processing (block 410). Telecom system 110 may for example, determine which telephone numbers are “available” (e.g., currently unassigned) and which telephone number are “unavailable” (e.g., currently assigned) for assignment. A telephone number may be identified for processing based on or irrespective of its availability status. In one embodiment, telecom system 100 may group subscriber numbers (“xxxx”) by a particular area code (“NPA”) and/or particular exchange (“NXX”) for processing. For example, letter mapping logic 320 may convert the digits of telephone numbers NPA-XXX-0000 to NPA-XXX-9999 into their respective series of alphabet and/or alphanumeric strings (“strings”) (block 415).
Term identification/matching logic 330 may identify letter sequences, in the strings, to determine letter sequences that fully or at least partially match one or more recognized terms (block 420). Upon locating a term in a string, term identification/matching logic 330 may determine whether the number of letters remaining in the string are less than or greater than a minimum term length (block 425). When the number of letters remaining in the string equal or exceed the minimum length (block 425—YES), term identification/matching logic 330 may identify additional terms in the remaining letters (block 420). When the number of letters remaining in the string are less than the minimum length (block 425—NO), term identification/matching logic 330 may provide the identified term(s) to scoring logic 340 for scoring (block 430).
As discussed above, scoring logic 340 may score the identified terms and the associated respective scores for the strings, using one or more scoring metrics. In one embodiment, scoring may account for the length of (i.e., number of letters in) a term, and the number of terms in a string. For example, a score, V, may be computed according to the following equation:
V=L
1
2
+L
2
2
+ . . . +L
n
2 (Eq. 1)
where L is the number of letters in a term, and L2 may correspond to a term score or an intermediary score. In this example, with a 2-letter term minimum in place, and a 10-letter term maximum in place, Vmin=4 and Vmax=100.
Another example of a metric for computing a score, V, is given by the following equation:
V=(0.5*(1−Du/10)+0.025*(10−Pt+1)+0.025*√(T12+T22+ . . . Tn2))*100 (Eq. 2)
where Du is the number of unused letters in a string,
where Pt is the position of a first letter of a first term in a string, with respect to a left-most letter of the string, and
where T is the number of terms in the string. In this example, with a 10-letter term maximum in place, Vmax=100. The above metric generally weights the number of letters used by a factor of 0.5, the position of the first occurring term by a factor of 0.25, and the number of terms by a factor of 0.25. Other weighting is possible.
It will be appreciated that the above scoring metrics may be modified and other scoring models may be used. Consistent with embodiments described herein, letters extending beyond a final letter of a string in order to complete a term (as discussed above), may be counted or discounted for scoring purposes. In one embodiment, when multiple scoring metrics are used, the metrics may have a minimum value, a mid-range value, a maximum value, and/or any other value in common. In some embodiments, scores computed using each metric may include intermediary scores that are combined to calculate an overall score.
In other embodiments, scores computed for respective strings associated with a particular telephone number may include intermediary scores that are combined to calculate an overall score for the particular telephone number. In still other embodiments, any of the above-discussed scores may be used to establish a fee schedule related to telephone number assignment, for example, by imposing fees on subscribers for selecting a telephone number having an associated score within a particular range of scores.
In one embodiment, scores may be compared to a threshold value, for example, by threshold determination logic 350 (block 470). The threshold value may be dynamically adjusted based on a number of criteria, such as user-specific information provided, a state of database storage space, etc.
Consistent with embodiments described herein, results of the comparison of the scores to the threshold value may be used to determine which of the strings are to be stored in a database, in association with the corresponding telephone numbers, in a retrievable state responsive to a search query (block 480); and which of the strings are not to be stored, in association with the corresponding telephone numbers, and thereby unsearchable/irretrievable (block 490). Processing may include searching the telephone number inventory based on a particular string score and/or range of scores, for example, specified in a query received from a user. Search results may be output to the user, with or without presenting the scores, in the form of telephone numbers and/or the corresponding mnemonic terms. In one implementation, the mnemonic terms may be presented as a list, for example, ordered or sorted based on the respective scores and/or ranges of respective scores.
By way of example, assume that the telephone number provided for processing is the 10-digit number, 466-472-4665. Using telephone keypad letter mapping, in which “4” corresponds to “GHI,” “6” corresponds to “MNO,” etc., letter mapping logic 320 (
Scoring logic 340 (
Assume now that the mathematical expression given by Eq. 2 above is used in scoring the strings. For example, HOMESCHOOL, having a term length of 10 letters, yields a score of 100, corresponding to (i.e., 0.5*(1−0/10)+0.025*(10−1+1)+0.025*√102)*100; GOOD-SCHOOL a score of 93 (i.e., 0.5*(1−0/10)+0.025*(10−1+1)+0.025*√(42+62))*100); and so on. In one implementation, term identification/matching logic 330 may treat the scores determined using Eq. 1 and the scores determined using Eq. 2 as intermediary scores. In this embodiment, term identification/matching logic 330 may combine the corresponding scores in any manner to determine an overall score. For example, HOMESCHOOL may have an overall score of 100 (i.e., (100+100)/2); GOOD-SCHOOL may have an overall score of 72.5 (i.e., (93+52)/2); and so on. Other methods of computing the overall scores may be used.
Threshold determination logic 350 may determine a threshold to be used in determining which of strings to store in a database in association with the telephone number, 466-472-4665. Assume that a threshold of 40 is determined. Scoring/search logic 360 may compare the above scores to the threshold of 40. Based on the comparison, scoring/search logic 360 may determine that the scores for the strings HOMESCHOOL (100), HOMESCHOOLING (100), GOOD-SCHOOL (52), GOOD-SCHOOLING (52), HOODS-2-HOOK (41 or 45) exceed the threshold (40); and that the scores for the strings HOODS (25) and GOODS (25) are less than the threshold (40).
Based on the above results, scoring/search logic 360 may determine to store the strings HOMESCHOOL, HOMESCHOOLING, GOOD-SCHOOL, GOOD-SCHOOLING, and HOODS-2-HOOK in a database; and not to store the strings HOODS and GOODS.
Scoring/search logic 360 may perform, responsive to a query, a search of database 500 based on a threshold of 50, for example, determined by threshold determination logic 350 based on the query. Scoring/search logic 360 may return the strings, HOMESCHOOL, HOMESCHOOLING, GOOD-SCHOOL, and GOOD-SCHOOLING based on the search. Assume that user-specific information contained in the query may indicate that the term “good” is particularly relevant to the user. Based on the user-specific information, scoring/search logic 360 may re-arrange an order of the returned strings to list the strings GOOD-SCHOOL and GOOD-SCHOOLING first, even though their scores are lower than the scores for the strings HOMESCHOOL and HOMESCHOOLING. Other modifications may be performed with respect to presentation of the strings based on user-specific or other types of information. In one implementation, scoring/search logic 360 may indicate to the user, a fee associated with allocation of the telephone number, 466-472-4665, based on the one or more of the above scores and/or a combination of one or more of the above scores.
Implementations described herein relate to devices, methods, and systems for using telephone number mnemonics with respect to maintaining a manageable telephone number inventory. In some implementations, a telecom system may include components configured to maintain searchable information regarding telephone number mnemonics with respect to allocating telephone numbers from a telephone number inventory.
The foregoing description of exemplary implementations provides illustration and description, but is not intended to be exhaustive or to limit the embodiments described herein to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practice of the embodiments.
For example, various features have been mainly described above with respect to a telecom system performing telephone number processing and storing functions. In other implementations, features described herein may be implemented mainly in one or more devices remote from the telecom system, or by an individual, workstation, and/or company associated with the telecom system.
Further, while series of blocks have been described with respect to
It will also be apparent that various features described above may be implemented in many different forms of software, firmware, and hardware in the implementations illustrated in the figures. The actual software code or specialized control hardware used to implement the various features is not limiting. Thus, the operation and behavior of the features of the invention were described without reference to the specific software code—it being understood that one would be able to design software and control hardware to implement the various features based on the description herein.
Further, certain features described above may be implemented as “logic” that performs one or more functions. This logic may include hardware, such as one or more processors, microprocessors, application specific integrated circuits, or field programmable gate arrays, software, or a combination of hardware and software.
In the preceding specification, various preferred embodiments have been described with reference to the accompanying drawings. It will, however, be evident that various modifications and changes may be made thereto, and additional embodiments may be implemented, without departing from the broader scope of the invention as set forth in the claims that follow. The specification and drawings are accordingly to be regarded in an illustrative rather than restrictive sense.
No element, act, or instruction used in the description of the present application should be construed as critical or essential to the invention unless explicitly described as such. Also, as used herein, the article “a” is intended to include one or more items. Where only one item is intended, the term “one” or similar language is used. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise.
