Method, computer program product and electronic device for hyper-local geo-targeting

Abstract
A method, computer program product and electronic device are provided for providing hyper-local geo-targeting based on validated, user-supplied geographic information, wherein the user's anonymity may be maintained. In particular, user-supplied geographic information may be collected in association with a truncated IP address. Once collected, the user-supplied information may be validated using geographic data previously derived from one or more complete IP addresses corresponding to the received truncated IP address. The derived geographic data may have been derived using a system that maps the routing infrastructure of the Internet in order to determine where endpoints on the Internet are located. The validated, user-supplied geographic information, which may be more specific than the derived geographic data, may then be used to provide more granular and accurate geo-targeting, all the while maintaining the privacy of the individual users.
Description
FIELD

Embodiments of the invention relate, generally, to geo-targeting and, in particular, to hyper-local IP targeting based on validated, user-provided geographic information.


BACKGROUND

The Internet consists of a network of interconnected computer networks. Each of these computers has an Internet Protocol (IP) address that is comprised of a series of four numbers (or octets) separated by periods or dots, wherein each of these four numbers is an 8-bit integer which collectively represent the unique address of the computer within the Internet. The Internet is a packet switching network whereby a data file routed over the Internet to some destination is broken down into a number of packets that are separately transmitted to the destination. Each packet contains, inter alia, some portion of the data file and the IP address of the destination.


The IP address of a destination is useful in routing packets to the correct destination, but it is not very people friendly. In particular, a group of four 8-bit numbers by themselves do not reveal or suggest anything about the destination, and most people would likely find it difficult to remember the IP addresses of a destination. As a result of this shortcoming in just using IP addresses, domain names were created.


Domain names consist of two or more parts, frequently words, separated by periods. Since the words, numbers, or other symbols forming a domain name often indicate or at least suggest the identity of a destination and are more easily remembered than the IP address, domain names have become the standard way of entering an address.


After a domain name has been entered, a domain name server (DNS) resolves the domain name into a specific IP address. Thus, for example, when someone surfing the Internet enters into a browser program a particular domain name for a web site, the browser first queries the DNS to arrive at the proper IP address.


While the IP address works well to deliver packets to the correct address on the Internet, IP addresses do not convey any useful information about the geographic address of the destination. Furthermore, the domain names do not even necessarily indicate any geographic location, though sometimes they may suggest, correctly or incorrectly, such a location.


Systems have been developed that enable entities, such as advertising networks, web publishers, search engines, social networks, e-tailers, and/or the like, who find it useful to know a user's geographic location, to derive the user's location from his/her IP address. These entities may then use this information for a variety of applications including, for example, delivering geo-targeted advertisements, localizing online storefronts, controlling the distribution of online content or goods, and/or the like. An example of such a system is that described in U.S. Pat. No. 6,757,740, entitled “Systems and Methods for Determining Collecting and Using Geographic Locations of Internet Users” (“the '740 patent”), which is commonly assigned to the assignee of the present application, and which is incorporated herein by reference in its entirety. The techniques of the '740 patent are discussed in more detail below.


As marketers and other entities continue to embrace the value that IP intelligence (i.e., geographic information derived from IP addresses) brings to online endeavors, however, they are also demanding more granularity. In particular, while country-level location information may have been sufficient before, greater depth and accuracy of location information is gradually becoming more and more desired in order to enable companies to build a true one-to-one relationship with a growing online audience.


This desire for more granular and accurate geographic location information associated with users is countered, however, by the privacy concerns of those users who may not want their name and address linked to their IP address and subsequently used, for example, for advertising purposes. In fact, communication of such user-specific information may violate various privacy laws in place in different countries.


A need, therefore, exists for a technique for obtaining more specific geographic information associated with an IP address without violating any privacy issues.


BRIEF SUMMARY

In general, embodiments of the present invention provide an improvement by, among other things, providing a method, computer program product, system and electronic device for providing hyper-local (e.g., zip code level) geo-targeting based on validated, user-provided geographic information, wherein the user's anonymity may be maintained. In particular, according to one embodiment, anonymous, user-supplied geographic information may be collected in association with a truncated IP address (e.g., the first three octets of a complete IP address). Since a complete IP address is not used, the user-supplied geographic information cannot be linked to a specific user. Instead, the information supplied could apply to any one of 255 different users having the same truncated IP address. As a result, according to embodiments of the present invention, a user's anonymity may be maintained.


Once collected, the user-supplied information may be validated using geographic data previously derived from one or more complete IP addresses corresponding to the received truncated IP address (e.g., IP addresses having the same first three octets). In one embodiment, this geographic data may, for example, have been derived using a system that maps the routing infrastructure of the Internet in order to determine where endpoints on the Internet are located.


The derived geographic data, while useful, may not be as specific as the user-supplied geographic information. For example, the derived geographic data may only indicate a city or state associated with the IP address, while the user-supplied geographic information may include a postal or zip code. As a result, once the user-supplied geographic information has been validated, according to embodiments of the present invention, this validated, user-supplied geographic information may be used to provide more granular and accurate geo-targeting, all the while maintaining the privacy of the individual users.


In accordance with one aspect, a method is provided of hyper-local geo-targeting based on validated, user-provided geographic information, wherein the user's anonymity may be maintained. In one embodiment, the method may include: (1) receiving, by a computer over a network, a truncated IP address associated with a user; (2) receiving, by the computer, user-supplied geographic information associated with the truncated IP address; (3) retrieving, by the computer from a database, geographic data derived from one or more complete IP addresses corresponding to the truncated IP address; and (4) validating, by the computer, the user-supplied geographic information based at least in part on the derived geographic data, wherein, once validated, the user-supplied geographic information can be used to provide geo-targeted information.


According to another aspect, an electronic device is provided for hyper-local geo-targeting based on validated, user-provided geographic information. In one embodiment, the electronic device may include a processor configured to: (1) receive a truncated IP address associated with a user; (2) receive user-supplied geographic information associated with the truncated IP address; (3) retrieve, from a database, geographic data derived from one or more complete IP addresses corresponding to the truncated IP address; and (4) validate the user-supplied geographic information based at least in part on the derived geographic data, wherein, once validated, the user-supplied geographic information can be used to provide geo-targeted information.


In accordance with yet another aspect, a computer program product is provided for hyper-local geo-targeting based on validated, user-provided geographic information. The computer program product contains at least one computer-readable storage medium having computer-readable program code portions stored therein. The computer-readable program code portions of one embodiment may include: (1) a first executable portion for receiving a truncated IP address associated with a user; (2) a second executable portion for receiving user-supplied geographic information associated with the truncated IP address; (3) a third executable portion for retrieving, from a database, geographic data derived from one or more complete IP addresses corresponding to the truncated IP address; and (4) a fourth executable portion for validating the user-supplied geographic information based at least in part on the derived geographic data, wherein, once validated, the user-supplied geographic information can be used to provide geo-targeted information.





BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

Having thus described embodiments of the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:



FIG. 1 is a block diagram of one type of system that would benefit from embodiments of the present invention;



FIG. 2 is a schematic block diagram of an entity capable of operating as a Geo-Intelligence server in accordance with embodiments of the present invention;



FIG. 3 is a flow chart illustrating the process of providing hyper-local geo-targeting based on validated, user-supplied geographic information in accordance with embodiments of the present invention; and



FIG. 4 is a flow chart illustrating the process of deriving geographic data from an IP address in accordance with embodiments of the present invention.





DETAILED DESCRIPTION

Embodiments of the present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the inventions are shown. Indeed, embodiments of the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.


Overall System and Mobile Device


Referring to FIG. 1, an illustration of one type of system that may benefit from embodiments of the present invention is provided. As shown in FIG. 1, the system may include one or more user devices 10 (e.g., personal computers (PC's), laptops, personal digital assistants (PDA's), etc.) in communication with a network server 30 over a communication network 20 (e.g., wired or wireless personal area network (PAN), local area network (LAN), wide area network (WAN), etc.) for the purpose of conducting an online transaction in association with which the user provides some geographic information (e.g., city, state, zip code, etc.). For example, a user may use his or her computer 10 to purchase an item on eBay®, wherein the user's address is transmitted to a server 30 associated with eBay for the purpose of account verification, payment and/or shipping.


The system may further include a geo-intelligence server 40, and corresponding database 45, in communication with the network server 30 over the same or different communications network 20. In one embodiment, as discussed in more detail below with regard to FIG. 3, the geo-intelligence server 40 may be configured to receive the user-supplied geographic information along with a truncated IP address associated with the user (e.g., the first three octets of a complete IP address) from the network server 30, validate the user-supplied geographic information using geographic data previously derived from IP addresses corresponding to the truncated IP address received, and then use the user-supplied geographic information for subsequent geo-targeting.


Referring now to FIG. 2, a block diagram of an entity capable of operating as a geo-intelligence server 40 is shown in accordance with one embodiment of the present invention. The entity capable of operating as a geo-intelligence server 40 includes various means for performing one or more functions in accordance with embodiments of the present invention, including those more particularly shown and described herein. It should be understood, however, that one or more of the entities may include alternative means for performing one or more like functions, without departing from the spirit and scope of the present invention. As shown, the entity capable of operating as a geo-intelligence server 40 can generally include means, such as a processor 210 for performing or controlling the various functions of the entity.


In particular, the processor 210 may be configured to perform the processes discussed in more detail below with regard to FIG. 3. For example, according to one embodiment the processor 210 may be configured to receive a truncated IP address along with user-supplied geographic information associated with a user. The processor 210 may further be configured to retrieve geographic data derived from one or more complete IP addresses corresponding to the truncated IP address received, and to use the derived geographic data to validate the user-supplied geographic information. Once validated, the processor 210 may further be configured to store the user-supplied geographic information in the database 45 in association with the complete IP addresses for which the user-supplied geographic information has been validated (i.e., in replacement of the derived geographic data previously associated with those IP addresses). The processor 210 may subsequently use the user-supplied geographic information to provide geo-targeted information in response to requests received in association with those complete IP addresses.


In one embodiment, the processor is in communication with or includes memory 220, such as volatile and/or non-volatile memory that stores content, data or the like. For example, the memory 220 may store content transmitted from, and/or received by, the entity. Also for example, the memory 220 may store software applications, instructions or the like for the processor to perform steps associated with operation of the entity in accordance with embodiments of the present invention. In particular, the memory 220 may store software applications, instructions or the like for the processor to perform the operations described above and below with regard to FIG. 3 for providing hyper-local geo-targeting based on validated, user-supplied geographic information.


For example, according to one embodiment, the memory 120 may store one or more modules for instructing the processor 210 to perform the operations including, for example, a user-information module, a derived-information module, a validation module, and a geo-targeting module. In one embodiment, the user-information module may be configured to instruct the processor 210 to receive the truncated IP address (e.g., 24.2.53.X) and user-supplied geographic information (e.g., zip code 30307) associated with a user. The derived-information module may be configured to then instruct the processor 210 to retrieve geographic data derived from one or more complete IP addresses corresponding to the truncated IP address received (e.g., 24.2.53.0-100, 24.2.53.210, etc.). In one embodiment, the derived-information module may further be configured to instruct the processor 210 to derive geographic data from one or more complete IP addresses, for example, in a manner described below involving mapping the routing infrastructure of the Internet.


Once the derived geographic data has been retrieved, the validation module may be configured to instruct the processor 210 to use the derived geographic data to validate the user-supplied geographic information. Finally, the geo-targeting module may be configured to instruct the processor 210 to store the validated user-supplied geographic information in the database 45 in association with the complete IP addresses for which the user-supplied geographic information has been validated, and then use the user-supplied geographic information to provide geo-targeted information in response to requests received in association with those complete IP addresses.


In addition to the memory 220, the processor 210 can also be connected to at least one interface or other means for displaying, transmitting and/or receiving data, content or the like. In this regard, the interface(s) can include at least one communication interface 230 or other means for transmitting and/or receiving data, content or the like, as well as at least one user interface that can include a display 240 and/or a user input interface 250. The user input interface, in turn, can comprise any of a number of devices allowing the entity to receive data from a user, such as a keypad, a touch display, a joystick or other input device.


While the foregoing description refers to a geo-intelligence “server,” as one of ordinary skill in the art will recognize in light of this disclosure, embodiments of the present invention are not limited to a server-client architecture. Instead, the geo-intelligence “server” may comprise any electronic device capable of performing the functionality described herein. Similarly, as one of ordinary skill in the art will recognize in light of this disclosure, the functionality described herein as being performed by the geo-intelligence server may be performed by a single, or multiple electronic devices or entities operating alone or in association with one another.


Method of Providing Hyper-Local Geo-Targeting


Referring now to FIG. 3, the operations are illustrated that may be taken in order to provide hyper-local (e.g., zip code level) geo-targeting based on validated, user-supplied geographic information, wherein the user's anonymity may be maintained. As shown, the process may begin at Blocks 301 and 302 when the geo-intelligence server 40 (e.g., a processor, or similar computing device, associated with the server and executing, for example, the user-information module) receives a truncated IP address and user-supplied geographic information associated with a user.


In one embodiment, the truncated IP address and user-supplied geographic information may be received, for example, from a network server 30, or similar device, associated with any company or entity that conducts online transactions with a user whereby the user provides some location information. For example, a company, such as eBay®, Yahoo®, AOL®, and/or the like, may receive address or location information from a user for the purpose of establishing or verifying an account, billing for products or services purchased, providing delivery information for a product purchased, and/or the like. The address or location information may include, for example, the user's street address, city, state and/or zip code (e.g., 664 N. Highland Avenue NE; Atlanta, Ga. 30307). According to embodiments of the present invention, the company may, thereafter, transmit the user-supplied geographic information, along with a truncated IP address associated with the user, to the geo-intelligence server 40.


In one embodiment, the truncated IP address may include the first three octets of a complete IP address associated with the user, wherein the complete IP address has four octets. To illustrate, an example of a truncated IP address may be 24.2.53.X, where the complete IP addresses that correspond to that truncated IP address include any IP address having the same first three octets (i.e., IP addresses 24.2.53.0 to 24.2.53.255). Because the truncated IP address could correspond to any one of 255 different IP addresses having the same first three octets and, therefore, any one of up to 255 different users, a user cannot be specifically identified by the truncated IP address. As a result, by transmitting only a truncated IP address (as opposed to the complete IP address associated with the user), embodiments of the present invention maintain the user's anonymity and avoid any privacy issues associated with transmitting user-specific information.


Once the truncated IP address and user-supplied geographic information have been received, according to one embodiment, the geo-intelligence server 40 (e.g., a processor, or similar computing device, associated with the server and executing, for example, the derived-information module) may, at Block 303, access a database 45 to retrieve geographic data that has been derived from one or more complete IP addresses corresponding to the received truncated IP address. In other words, the geo-intelligence server 40 may retrieve any geographic data derived from a complete IP address having the same first three octets as the received truncated IP address. Continuing with the example above, upon receipt of the truncated IP address 24.2.53.X, the geo-intelligence server 40 may access the database 45 to retrieve any geographic data that has been derived from any one or more of the complete IP addresses ranging from 24.2.53.0 to 24.2.53.255.


According to one embodiment, the geographic data may have been derived from the complete IP address in a manner similar to that described in U.S. Pat. No. 6,757,740, entitled “Systems and Methods for Determining Collecting and Using Geographic Locations of Internet Users” (“the '740 patent”). In general, according to one of the methods described in the '740 patent, the geo-intelligence server may use various Internet route tools to aid in discovering the likely placement of a newly discovered Internet host (i.e., a target host corresponding to an IP address). These tools may include, for example, programs such as nslookup, ping, traceroute, and whois.


In particular, according to one embodiment, the following process, which is also shown in FIG. 4, may be used in order to derive geographic data from a complete IP address associated with a target host. First, the geo-intelligence server may receive a new IP address, for which geographic data is desired. (Block 401). Upon receipt, the IP address and, in one embodiment, a domain name associated with the IP address may be verified using, for example, nslookup. (Block 402). As one of ordinary skill in the art will recognize in light of this disclosure, in order to verify an IP address and/or domain name, nslookup converts IP addresses to domain names, and vice versa, using the Domain Name Server (DNS) lookup system.


Once verified, the geo-intelligence server may, at Block 403, determine whether the target host is online and operational by sending a request to the target host using, for example, ping. If it is determined that the target host is not online, according to one embodiment, the process may continue to check until the host is online and operational. Once online and operational, the geo-intelligence server may, at Block 404, determine the ownership of the domain name and/or IP address associated with the target host. In one embodiment, this may be done using, for example, whois. In particular, according to one embodiment, whois may query one or more servers on the Internet to obtain registration information, including a geographic address, for the domain name and/or a block of IP addresses including the target host IP address. While the geographic address included in the registration information may not necessarily be the location of the IP address, this information may be useful for smaller organizations whose IP blocks are often geographically in one location (i.e., small whois block, discussed below).


The geo-intelligence server may then, at Block 405, determine the route taken to reach the target host. In particular, according to one embodiment, the geo-intelligence server may use traceroute, which may provide the IP address and domain name for each host encountered from the source host to the target host, wherein the source host corresponds to the geo-intelligence server.


Once each of the intermediate hosts has been identified (at Block 405), the geo-intelligence server may, at Block 406, determine the geographic location associated with each of those intermediate hosts, as well as the confidence level (e.g., between 0 and 100) assigned to that geographic location. This may involve, for example, accessing a database to retrieve previously derived geographic data and confidence information associated with the intermediate host. If, however, the geographic location of an intermediate host is unknown, the location may be derived, and a confidence level assigned, using, for example, the technique described below with regard to Block 407.


Once the geographic location of each intermediate host has been determined, the geo-intelligence server may, at Block 407, determine the location of the target host and assign a confidence level to that determination based at least in part on the locations of the intermediate hosts and the confidence level associated with those locations. All new hosts (intermediate and target) and their corresponding geographic data may then be added to the database. In particular, in one embodiment, once the geographic data has been derived from a complete IP address, or range of complete IP addresses, the geographic data may be stored in the database 45 in association with the corresponding IP address(es). For example, the database may store an entry that links “Atlanta” to the IP addresses ranging from 24.2.53.0 to 24.2.53.100, along with another entry that links “San Francisco” to the IP addresses ranging from 24.2.53.101 to 24.2.53.255. It is the information in these entries (i.e., “Atlanta” and “San Francisco”) that the geo-intelligence server 40 may retrieve at Block 303 in response to receiving the truncated IP address 24.2.53.X.


According to embodiments described herein, in order to derive the geographic data from a received IP address, in addition to using the geographic location of the intermediate hosts in the route associated with the target host, a combination of several different factors may be used to determine the geographic location of the target, as well as to assign a confidence level to that geographic location. For example, according to one embodiment, the whois registration information (i.e., the address information provided by the domain name/IP address registrant) may be used to help determine the geographic location, though the confidence level associated with the determined location may be relatively low (e.g., 35). Alternatively, or in addition, mapping information provided by an Internet Service Provider (ISP) in association with an IP address may further be used.


In one embodiment, the geographic information associated with neighboring IP addresses may likewise be used. For example, if the database 45 includes geographic information for IP addresses immediately before and/or after the complete IP address, it may be assumed that the IP address has the same, or similar, geographic location.


In addition, the geo-intelligence server 40 may take advantage of common naming conventions in order to make reasonable guesses as to the geographic locations of the hosts. For example, any host that contains “sanjose” in the first part of its domain name is probably located in San Jose, Calif. or connected to a system that is in San Jose, Calif. In one embodiment, the database 45 may have lookup tables that list geographic locations, such as city, county, regional, state, and/or the like, with corresponding variations of the names. For example, the database 45 may have multiple listings for San Francisco, Calif. including, for example, “SanFrancisco,” “SanFran,” “Sfrancisco,” and/or the like. The geo-intelligence server 40 may access the database to retrieve any geographic location information associated with at least part of the domain name and use this to make a guess as to the geographic location of the target host.


As an example, a sample search to determine the geographic location of the domain name “digitalenvoy.net” will now be described. First, the geo-intelligence server 40 may receive the domain name “digitalenvoy.net” associated with the target host (Block 401) and perform a DNS lookup on the name (Block 402). In response, the command nslookup may return the following to the geo-intelligence server 40:


nslookup digitalenvoy.net


Name: digitalenvoy.net


Address: 209.153.199.15


The geo-intelligence server 40 may then, at Block 403, perform a ping on the target host machine, which may tell the geo-intelligence server 40 if the target host is on-line and operational. In this example, the ping may return the following to the geo-intelligence server 40, indicating that the target host is online and operational:














ping -c 1 digitalenvoy.net


PING digitalenvoy.net (209.153.199.15): 56 data bytes


64 bytes from 209.153.199.15: icmp_seq=0 ttl=241 time=120.4 ms


--- digitalenvoy.net ping statistics ---


1 packets transmitted, 1 packets received, 0% packet loss


round-trip min/avg/max = 120.4/120.4/120.4 ms









Continuing with FIG. 4, the geo-intelligence server 40 may then execute a whois on “digitalenvoy.net” to determine ownership of the domain name. (Block 404). In this example, the whois may inform the geo-intelligence server 40 that the registrant is in Georgia.














> whois digitalenvoy.net


Registrant:


Some One (DIGITALENVOY-DOM)









1234 Address Street



ATLANTA, GA 33333



US



Domain Name: DIGITALENVOY.NET



Administrative Contact:









One, Some (SO0000) some@one.net



+1 404 555 5555









Technical Contact, Zone Contact:









myDNS Support (MS311-ORG) support@MYDNS.COM



+1 (206) 374.2143









Billing Contact:









One, Some (SO0000) some@one.net



+1 404 555 5555









Record last updated on 14-Apr-99.



Record created on 14-Apr-99.



Database last updated on 22-Apr-99 11:06:22 EDT.



Domain servers in listed order:










NS1.MYDOMAIN.COM
209.153.199.2



NS2.MYDOMAIN.COM
209.153.199.3



NS3.MYDOMAIN.COM
209.153.199.4



NS4.MYDOMAIN.COM
209.153.199.5









The geo-intelligence server 40 may then execute a traceroute on the target host to determine the route taken to reach the target host. (Block 405). In this example, the traceroute on “digitalenvoy.net” may return the following to the geo-intelligence server 40:














> traceroute digitalenvoy.net


traceroute to digitalenvoy.net (209.153.199.15), 30 hops max, 40


byte packets









 1 130.207.47.1 (130.207.47.1) 6.269 ms 2.287 ms 4.027 ms



 2 gateway1-rtr.gatech.edu (130.207.244.1) 1.703 ms 1.672 ms







1.928 ms









 3 f1-0.atlanta2-cr99.bbnplanet.net (192.221.26.2) 3.296 ms







3.051 ms 2.910 ms









 4 f1-0.atlanta2-br2.bbnplanet.net (4.0.2.90) 3.000 ms







3.617 ms 3.632 ms









 5 s4-0-0.atlanta1-br2.bbnplanet.net (4.0.1.149) 4.076 ms







s8-1-0.atlanta1-br2.bbnplanet.net (4.0.2.157) 4.761 ms 4.740 ms









 6 h5-1-0.paloalto-br2.bbnplanet.net (4.0.3.142) 72.385 ms







71.635 ms 69.482 ms









 7 p2-0.paloalto-nbr2.bbnplanet.net (4.0.2.197) 82.580 ms







83.476 ms 82.987 ms









 8 p4-0.sanjose1-nbr1.bbnplanet.net (4.0.1.2) 79.299 ms







78.139 ms 80.416 ms









 9 p1-0-0.sanjose1-br2.bbnplanet.net (4.0.1.82) 78.918 ms







78.406 ms 79.217 ms









10 NSanjose-core0.nap.net (207.112.242.253) 80.031 ms







78.506 ms 122.622 ms









11 NSeattle1-core0.nap.net (207.112.247.138) 115.104 ms







112.868 ms 114.678 ms









12 sea-atm0.starcom-accesspoint.net (207.112.243.254)







112.639 ms 327.223 ms 173.847 ms









13 van-atm10.10.starcom.net (209.153.195.49) 118.899 ms







116.603 ms 114.036 ms









14 hume.worldway.net (209.153.199.15) 118.098 ms * 114.571 ms









The geo-intelligence server 40 may, at Block 406, determine the geographic locations of each of the intermediate hosts in the determined route, as well as a confidence level associated with each of those geographic locations. As discussed above, in one embodiment, this may involve accessing the database 45 to retrieve the previously derived geographic location information for each intermediate host. Using this information, as well as other factors (e.g., the whois registration information, naming conventions, etc.), the geo-intelligence server 40 may, at Block 407, determine the geographic location of the target host, and a confidence level associated therewith. The following provides an example of the geographic information and confidence level for the intermediate and target hosts according to this example:


















130.207.47.1 (130.207.47.1)
Host machine located in




Atlanta, GA



gateway1-rtr.gatech.edu
Atlanta, GA - confidence 100



(130.207.244.1)




f1-0.atlanta2-cr99.bbnplanet.net
Atlanta, GA - confidence 100



(192.221.26.2)




f1-0.atlanta2-br2.bbnplanet.net
Atlanta, GA - confidence 95



(4.0.2.90)




s4-0-0.atlanta1-br2.bbnplanet.net
Atlanta, GA - confidence 80



(4.0.1.149)




h5-1-0.paloalto-br2.bbnplanet.net
Palo Alto, CA - confidence 85



(4.0.3.142)




p2-0.paloalto-nbr2.bbnplanet.net
Palo Alto, CA - confidence 90



(4.0.2.197)




p4-0.sanjose1-nbr1.bbnplanet.net
San Jose, CA - confidence 85



(4.0.1.2)




p1-0-0.sanjose1-br2.bbnplanet.net
San Jose, CA - confidence 100



(4.0.1.82)




NSanjose-core0.nap.net
San Jose, CA - confidence 90



(207.112.242.253)




NSeattle1-core0.nap.net
Seattle, WA - confidence 95



(207.112.247.138)




sea-atm0.starcom-accesspoint.net
Seattle, WS - confidence 95



(207.112.243.254)




van-atm10.10.starcom.net
Vancouver, British Columbia



(209.153.195.49)
Canada - confidence 100



hume.worldway.net
Vancouver, British Columbia



(209.153.199.15)
Canada










Returning to FIG. 3, once geographic data derived from one or more complete IP addresses corresponding to the received truncated IP address (e.g., in the manner described above) have been retrieved from the database 45, the geo-intelligence server 40 (e.g., a processor, or similar computing device, associated with the server and executing, for example, the validation module) may, at Block 304, use the derived geographic data to determine whether the user-supplied geographic information is valid.


In one embodiment, the user-supplied geographic information may be considered valid if it is the same or equivalent to the geographic data derived from at least one complete IP address corresponding to the truncated IP address, wherein the user-supplied geographic information may be considered the same or equivalent to the derived geographic data if both identify or correspond to the same, or substantially the same, geographic location. For example, if, as in the example above, the user-supplied geographic information associated with the truncated IP address 24.2.53.X included the zip code 30307, and the geographic data derived from the IP address range 24.2.53.0-24.2.53.100 was Atlanta, then, according to one embodiment, the user-supplied geographic information (i.e., 30307) would be considered valid for the IP address range 24.2.53.0-24.2.53.100, since 30307 is a zip code in Atlanta. As one of ordinary skill in the art will recognize in light of this disclosure, the user-supplied geographic information may be valid for any number and combination of IP addresses within the range of IP addresses corresponding to the truncated IP address.


According to one embodiment, a number of different rules may be applied in order to determine whether the user-supplied geographic information is valid. For example, the validity of the user-supplied geographic information may depend upon the number of complete IP addresses for which the derived geographic data is the same or equivalent to the user-supplied geographic information (e.g., if >25 complete IP addresses with the same or equivalent derived geographic data, then valid). Alternatively, or in addition, validity may depend upon the number of consistent user-supplied geographic information received for the same truncated IP address (e.g., if >25 user's provide same city or zip code for same truncated IP address, then valid), the reliability of the sources of the user-supplied geographic information, and/or the age of the user-supplied geographic information (e.g., if >1 year old, then invalid).


As one of ordinary skill in the art will recognize in light of this disclosure, the foregoing provides only a few examples of rules that may be applied in order to determine whether user-supplied geographic information is valid based on geographic data derived from corresponding IP addresses. Other similar rules may likewise be used in combination with or instead of the rules provided herein. The foregoing is, therefore, provided for exemplary purposes only and should not be taken in any way as limiting embodiments of the present invention to the examples provided.


If it is determined, at Block 304, that the user-supplied geographic information is not valid for any IP address that corresponds to the truncated IP address received, then the process ends. (Block 305). If, on the other hand, it is determined that the user-supplied geographic information is valid for at least one complete IP address, then the geo-intelligence server 40 (e.g., a processor, or similar computing device, associated with the server) may, at Block 306, update the database 45 by replacing the geographic data derived from that at least one complete IP address with the user-supplied geographic information. Continuing with the example above, the database 45 may be updated to replace the geographic data derived from IP address range 24.2.53.0-24.2.53.100 (i.e., Atlanta) with the more specific user-supplied geographic information (i.e., zip code 30307).


In one embodiment, there may be certain instances where the derived geographic data may be considered more reliable and/or accurate than the user-supplied geographic information, despite the user-supplied geographic information having been validated. For example, if the derived geographic data is based on the geographic address, including a zip code, provided by a company having registered a small range of IP addresses (e.g., <255) (i.e., a small whois range), the geographic address provided may be assumed to be valid for that range of IP addresses, since it is likely that the company only has one office corresponding to the geographic address provided. Because the geographic address is assumed valid, and is likely as specific as the user-supplied geographic information, it may be unnecessary to replace the geographic address with the user-supplied geographic information. This is in contrast to a company that registers a large range of IP addresses (e.g., >255) using the same geographic address. Because the company likely has multiple different offices at multiple different locations, the geographic address provided cannot be assumed to correspond to each of the registered IP addresses. Accordingly, the validated user-supplied geographic information may be used in this instance.


According to embodiments described herein, a similar decision not to replace the derived geographic data with the validated user-supplied geographic information may be made if, for example, the derived geographic data has been confirmed by a person and/or is based on automated modem calls into an Internet Service Provider (ISP) pop, wherein it is determined what IP's are allocated to the pop.


Other instances in which the user-supplied geographic information may not be used may include, for example, when a satellite connection has been used by the user (since the user-supplied geographic information is likely inaccurate), when the derived geographic data includes multiple best guest cities and/or host match cities in the range of IP addresses corresponding to the truncated IP address (i.e., using a point higher up in a trace route to determine user location when there is no other information closer to the end user), and/or when the user-supplied geographic information identifies a city (e.g., Atlanta), and the derived geographic data identifies a suburb of that city (e.g., Dunwoody) (since the suburb is likely more accurate).


According to one embodiment, the validated, user-supplied information, which, in one embodiment, may be more specific than the derived geographic data, may thereafter be used to provide hyper-local geo-targeting information. In particular, in one embodiment, the geo-intelligence server 40 (e.g., processor, or similar computing means, associated with the server and executing a geo-targeting module) may, at Block 307, receive a request for geographic information associated with a complete IP address for which the user-supplied geographic information has been validated and saved in the database 45 (e.g., 24.2.53.74). In one embodiment, the request may be received from a web server associated with a web site being accessed by a user, wherein the web server wishes to provide geo-targeted content (e.g., advertisements).


In response, the geo-intelligence server 40 (e.g., processor, or similar computing means, associated with the server and executing a geo-targeting module) may, at Block 308, provide the user-supplied geographic information stored in the database 45, such that this information may be used to provide geo-targeted information to the user. For example, as noted above, the geographic location information may be used, for example, by advertising networks, web publishers, search engines, social networks, e-tailers, and/or the like, who may use this information for a variety of applications including, for example, delivering geo-targeted advertisements, localizing online storefronts, controlling the distribution of online content or goods, and/or the like


CONCLUSION

As described above, embodiments of the present invention provide a method and system for providing hyper-local (e.g., zip code level) geo-targeting based on validated, user-supplied geographic information, wherein the user's anonymity may be maintained.


As described above and as will be appreciated by one skilled in the art, embodiments of the present invention may be configured as a method or device. Accordingly, embodiments of the present invention may be comprised of various means including entirely of hardware, entirely of software, or any combination of software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions (e.g., computer software) embodied in the storage medium. Any suitable computer-readable storage medium may be utilized including hard disks, CD-ROMs, optical storage devices, or magnetic storage devices.


Embodiments of the present invention have been described above with reference to block diagrams and flowchart illustrations of methods, apparatuses (i.e., systems) and computer program products. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus, such as processor 210 discussed above with reference to FIG. 2, to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create a means for implementing the functions specified in the flowchart block or blocks.


These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus (e.g., processor 210 of FIG. 2) to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including computer-readable instructions for implementing the function specified in the flowchart block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions that execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.


Accordingly, blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions or steps, or combinations of special purpose hardware and computer instructions.


Many modifications and other embodiments of the inventions set forth herein will come to mind to one skilled in the art to which these embodiments of the invention pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the embodiments of the invention are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Moreover, although the foregoing descriptions and the associated drawings describe exemplary embodiments in the context of certain exemplary combinations of elements and/or functions, it should be appreciated that different combinations of elements and/or functions may be provided by alternative embodiments without departing from the scope of the appended claims. In this regard, for example, different combinations of elements and/or functions than those explicitly described above are also contemplated as may be set forth in some of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

Claims
  • 1. A method comprising: receiving, by a computer over a network, a truncated internet protocol (IP) address associated with a user device related to a specific user;receiving, by the computer, user-supplied geographic information associated with the truncated IP address, the user-supplied geographic information not being linked to the specific user;retrieving, by the computer from a database, geographic data derived from one or more complete IP addresses corresponding to the truncated IP address;validating, by the computer, the user-supplied geographic information based at least in part on the geographic data, the validating comprising determining if the user-supplied geographic information is the same or equivalent to the derived geographic data associated with at least one of the one or more complete IP addresses corresponding to the truncated IP address, wherein in response to the user-supplied geographic information being validated, the user-supplied geographic information permits providing geo-targeted information.
  • 2. The method of claim 1, wherein a complete IP address comprises four octets, and the truncated IP address comprises the first three octets of the complete IP address.
  • 3. The method of claim 2, wherein the one or more complete IP addresses corresponding to the truncated IP address comprise one or more complete IP addresses having the same first three octets as the truncated IP address.
  • 4. The method of claim 1, wherein the user-supplied geographic information comprises one or more of street address, a zip code, a city, or a state associated with the specific user.
  • 5. The method of claim 1 further comprising: deriving geographic data from one or more complete IP addresses corresponding to the truncated IP address; andstoring the derived geographic data in the database in association with the one or more complete IP addresses.
  • 6. The method of claim 5, wherein deriving geographic data from the one or more complete IP addresses further comprises: identifying, for respective complete IP addresses, one or more intermediate hosts between a source host and a target host associated with the complete IP address;determining a geographic location associated with respective intermediate hosts; anddetermining a geographic location of the target host based at least in part on the geographic location of respective intermediate hosts.
  • 7. The method of claim 1, wherein the user-supplied geographic information is the same or equivalent to the derived geographic data when the user-supplied geographic information and the derived geographic data correspond to the same or equivalent geographic location.
  • 8. The method of claim 1, further comprising: identifying at least one complete IP address of the one or more complete IP addresses for which the derived geographic data is the same or equivalent to the user-supplied geographic information.
  • 9. The method of claim 8 further comprising: replacing the derived geographic data stored in the database in association with the at least one identified complete IP address with the user-supplied geographic information.
  • 10. The method of claim 9 further comprising: receiving, from a web server, a request for geographic information associated with a specific IP address of the at least one complete IP addresses; andtransmitting, to the web server, the user-supplied geographic information, that permits the web server to provide geo-targeted information to a user device associated with the specific IP address.
  • 11. The method of claim 1, wherein the determining step comprises applying a rule in order to determine the number of complete IP addresses of the one or more IP addresses having derived geographic data that is the same or equivalent to the user-supplied geographic information.
  • 12. A computer program product comprising at least one computer-readable non-transitory storage medium having computer-readable program code portions stored therein, said computer-readable program code portions comprising: a first executable portion for receiving a truncated internet protocol (IP) address associated with a user device related to a user;a second executable portion for receiving user-supplied geographic information associated with the truncated IP address, the user-supplied geographic information not being linked to the specific user;a third executable portion for retrieving, from a database, geographic data derived from one or more complete IP addresses corresponding to the truncated IP address;a fourth executable portion for validating the user-supplied geographic information based at least in part on the derived geographic data, the fourth executable portion being configured to determine whether the user-supplied geographic information is the same or equivalent to the derived geographic data associated with at least one of the one or more complete IP addresses corresponding to the truncated IP address, wherein in response to the user-supplied geographic information being validated, the user-supplied geographic information permits providing geo-targeted information.
  • 13. The computer program product of claim 12, wherein a complete IP address comprises four octets, and the truncated IP address comprises the first three octets of the complete IP address.
  • 14. The computer program product of claim 13, wherein the one or more complete IP addresses corresponding to the truncated IP address comprise one or more complete IP addresses having the same first three octets as the truncated IP address.
  • 15. The computer program product of claim 12, wherein the user-supplied geographic information comprises a zip code associated with the user.
  • 16. The computer program product of claim 12, wherein the computer-readable program code portions further comprise: a fifth executable portion for deriving geographic data from one or more complete IP addresses corresponding to the truncated IP address; anda sixth executable portion for storing the derived geographic data in the database in association with the corresponding complete IP addresses.
  • 17. The computer program product of claim 16, wherein the fifth executable portion is configured to: identify, for respective complete IP addresses, one or more intermediate hosts between a source host and a target host associated with the complete IP address;determine a geographic location associated with respective intermediate hosts; anddetermine a geographic location of the target host based at least in part on the geographic location of respective intermediate hosts.
  • 18. The computer program product of claim 12, wherein the user-supplied geographic information is the same or equivalent to the derived geographic data when the user-supplied geographic information and the derived geographic data correspond to the same or equivalent geographic location.
  • 19. The computer program product of claim 12, wherein the computer-readable program code portions further comprise: a fifth executable portion for identifying one or more of the complete IP addresses for which the derived geographic data is the same or equivalent to the user-supplied geographic information.
  • 20. The computer program product of claim 19, wherein the computer-readable program code portions further comprise: a sixth executable portion for replacing the derived geographic data stored in the database in association with the one or more identified complete IP addresses with the user-supplied geographic information.
  • 21. An electronic device comprising: a processor configured to: receive a truncated IP address associated with a user device related to a user;receive user-supplied geographic information associated with the truncated IP address, the user-supplied geographic information not being linked to the specific user;retrieve, from a database, geographic data derived from one or more complete IP addresses corresponding to the truncated IP address;validate the user-supplied geographic information based at least in part on the derived geographic data, wherein, once validated, the user-supplied geographic information permits providing geo-targeted information.
US Referenced Citations (158)
Number Name Date Kind
4939723 Harley, Jr. et al. Jul 1990 A
4939726 Flammer et al. Jul 1990 A
5042027 Takahashi et al. Aug 1991 A
5042032 Dighe et al. Aug 1991 A
5115433 Baran et al. May 1992 A
5231631 Buhrke et al. Jul 1993 A
5291550 Levy et al. Mar 1994 A
5418713 Allen May 1995 A
5421024 Faulk, Jr. et al. May 1995 A
5459863 Taylor Oct 1995 A
5488608 Flammer, III Jan 1996 A
5490252 Macera et al. Feb 1996 A
5493689 Waclawsky et al. Feb 1996 A
5636276 Brugger Jun 1997 A
5659596 Dunn Aug 1997 A
5680390 Robrock, II Oct 1997 A
5734651 Blakeley et al. Mar 1998 A
5734823 Saigh et al. Mar 1998 A
5734891 Saigh Mar 1998 A
5774668 Choquier et al. Jun 1998 A
5777989 McGarvey Jul 1998 A
5794217 Allen Aug 1998 A
5812865 Theimer et al. Sep 1998 A
5857191 Blackwell et al. Jan 1999 A
5870561 Jarvis et al. Feb 1999 A
5878126 Velamuri et al. Mar 1999 A
5913036 DeMoss et al. Jun 1999 A
5920697 Masters et al. Jul 1999 A
5930474 Dunworth et al. Jul 1999 A
5937163 Lee et al. Aug 1999 A
5944790 Levy Aug 1999 A
5946299 Blonder Aug 1999 A
5948061 Merriman et al. Sep 1999 A
5958052 Bellovin et al. Sep 1999 A
5963915 Kirsch Oct 1999 A
5974457 Waclawsky et al. Oct 1999 A
5978845 Reisacher Nov 1999 A
5987523 Hind et al. Nov 1999 A
6009081 Wheeler et al. Dec 1999 A
6012052 Altschuler et al. Jan 2000 A
6012088 Li et al. Jan 2000 A
6012090 Chung et al. Jan 2000 A
6014634 Scroggie et al. Jan 2000 A
6035332 Ingrassia, Jr. et al. Mar 2000 A
6058420 Davies May 2000 A
6069895 Ayandeh May 2000 A
6069939 Fung et al. May 2000 A
6091959 Souissi et al. Jul 2000 A
6108637 Blumenau Aug 2000 A
6119247 House et al. Sep 2000 A
6128664 Yanagidate et al. Oct 2000 A
6130890 Leinwand et al. Oct 2000 A
6148335 Robinson et al. Nov 2000 A
6151631 Ansell et al. Nov 2000 A
6167259 Shah Dec 2000 A
6192312 Hummelsheim Feb 2001 B1
6243746 Sondur et al. Jun 2001 B1
6243749 Sitaraman et al. Jun 2001 B1
6249252 Dupray Jun 2001 B1
6249813 Campion et al. Jun 2001 B1
6259701 Shur et al. Jul 2001 B1
6266607 Meis et al. Jul 2001 B1
6272150 Hrastar et al. Aug 2001 B1
6272343 Pon et al. Aug 2001 B1
6285660 Ronen Sep 2001 B1
6285748 Lewis Sep 2001 B1
6286047 Ramanathan et al. Sep 2001 B1
6317761 Landsman et al. Nov 2001 B1
6324585 Zhang et al. Nov 2001 B1
6327677 Garg et al. Dec 2001 B1
6330239 Suzuki Dec 2001 B1
6332127 Bandera et al. Dec 2001 B1
6332158 Risley et al. Dec 2001 B1
6343290 Cossins et al. Jan 2002 B1
6345303 Knauerhase et al. Feb 2002 B1
6347078 Narvaez-Guarnieri Feb 2002 B1
6356929 Gall et al. Mar 2002 B1
6374302 Galasso et al. Apr 2002 B1
6397246 Wolfe May 2002 B1
6415323 McCanne et al. Jul 2002 B1
6442565 Tyra et al. Aug 2002 B1
6446076 Burkey et al. Sep 2002 B1
6466940 Mills Oct 2002 B1
6473407 Ditmer et al. Oct 2002 B1
6477150 Maggenti et al. Nov 2002 B1
6484143 Swildens et al. Nov 2002 B1
6487538 Gupta et al. Nov 2002 B1
6498782 Branstad et al. Dec 2002 B1
6505201 Haitsuka et al. Jan 2003 B1
6505254 Johnson et al. Jan 2003 B1
6505255 Akatsu et al. Jan 2003 B1
6513061 Ebata et al. Jan 2003 B1
6516192 Spaur et al. Feb 2003 B1
6529475 Wan Mar 2003 B1
6529491 Chang et al. Mar 2003 B1
6542739 Garner Apr 2003 B1
6570974 Gerszberg et al. May 2003 B1
6571279 Herz et al. May 2003 B1
6574663 Bakshi et al. Jun 2003 B1
6577653 Rochberger et al. Jun 2003 B1
6578066 Logan et al. Jun 2003 B1
6597777 Ho Jul 2003 B1
6629136 Naidoo Sep 2003 B1
6643696 Davis et al. Nov 2003 B2
6665715 Houri Dec 2003 B1
6684250 Anderson et al. Jan 2004 B2
6721795 Eldreth Apr 2004 B1
6757740 Parekh et al. Jun 2004 B1
6778524 Augart Aug 2004 B1
6826617 Ansell et al. Nov 2004 B1
6973039 Redi et al. Dec 2005 B2
6996084 Troxel et al. Feb 2006 B2
7039689 Martija et al. May 2006 B2
7062572 Hampton Jun 2006 B1
7072963 Anderson et al. Jul 2006 B2
7116643 Huang et al. Oct 2006 B2
7139820 O'Toole et al. Nov 2006 B1
7200673 Augart Apr 2007 B1
7260085 Dobbins et al. Aug 2007 B2
7269157 Klinker et al. Sep 2007 B2
7296088 Padmanabhan et al. Nov 2007 B1
7298327 Dupray et al. Nov 2007 B2
7403978 Parekh et al. Jul 2008 B2
7451233 Parekh et al. Nov 2008 B2
7454523 Chow et al. Nov 2008 B2
7698377 Parekh Apr 2010 B2
7844729 Friedman Nov 2010 B1
8060606 Friedman Nov 2011 B2
20010020242 Gupta et al. Sep 2001 A1
20020007374 Marks et al. Jan 2002 A1
20020042274 Ades Apr 2002 A1
20020131363 Beshai et al. Sep 2002 A1
20020143991 Chow et al. Oct 2002 A1
20020152311 Veltman et al. Oct 2002 A1
20020165980 Brown Nov 2002 A1
20030031178 Haeri et al. Feb 2003 A1
20030086422 Klinker et al. May 2003 A1
20030090996 Stewart May 2003 A1
20030110293 Friedman Jun 2003 A1
20040078489 Anderson et al. Apr 2004 A1
20040078490 Anderson et al. Apr 2004 A1
20040151129 Kun-Szabo et al. Aug 2004 A1
20040199623 Houri Oct 2004 A1
20050021853 Parekh et al. Jan 2005 A1
20050041675 Trostle et al. Feb 2005 A1
20050190695 Phaal Sep 2005 A1
20050234922 Parekh Oct 2005 A1
20050251539 Parekh Nov 2005 A1
20050271038 Xin et al. Dec 2005 A1
20060146820 Friedman Jul 2006 A1
20060212601 Hampton Sep 2006 A1
20060224752 Parekh Oct 2006 A1
20080037536 Padmanabhan Feb 2008 A1
20080123558 Chhabra May 2008 A1
20080275978 Houri Nov 2008 A1
20090112703 Brown Apr 2009 A1
20100153525 Parekh Jun 2010 A1
20100211960 Sirajuddin et al. Aug 2010 A1
Foreign Referenced Citations (22)
Number Date Country
780066 Feb 2005 AU
2372808 Nov 2000 CA
1175767 Jan 2002 EP
10190603 Feb 2011 EP
09-284341 Oct 1997 JP
2011-032080 Feb 1999 JP
3254422 Jan 2000 JP
2000-201147 Jul 2000 JP
WO 9613108 May 1996 WO
WO 9934305 Jul 1999 WO
WO 0022495 Apr 2000 WO
WO 0067450 Nov 2000 WO
WO-0067450 Nov 2000 WO
WO 0122656 Mar 2001 WO
WO 0157696 Aug 2001 WO
WO 0157696 Aug 2001 WO
WO 0175632 Oct 2001 WO
WO 0213459 Feb 2002 WO
WO 0217139 Feb 2002 WO
WO 0223807 Mar 2002 WO
PCTUS201055240 Jan 2011 WO
WO 2011059862 May 2011 WO
Non-Patent Literature Citations (27)
Entry
Padmanabhan et al: “An Investigation of Geographic Mapping Techniques for Internet Hosts”,Computer Communication Review, ACM, New York, NY, US, vol. 31, No. 4, Oct. 1, 2001, Chapter 6: pp. 173-185.
Buyukkokten, Orkut , et al., “Exploiting Geographical Location Information of Web Pages” Department of Computer Science, Stanford University, Stanford, CA 94305; pp. 1-6. “Undated Reference, Applicant Admits as Prior Art”, Jan. 1999.
Cooney, R., “Subnet Addressing”, Network Computing, by www.networkcomputing.com/unixworld, tutoria1/001.html, “Undated Reference, Applicant Admits as Prior Art” submitted, Mar. 2010.
DeBellis, Mathew A.; “Digital Envoy Greets $1.1 Million;” VC & Startups; http://www.redherring.com/vc/2000/0229/vc-digitalenvoy022900.html; Feb. 29, 2000; 3 pages.
Digital Island; “Content Delivery Services: Footprint™ Streaming Solutions;” Digital Island, San Francisco, CA 64105 USA; (8 pp); “Undated Reference, Applicant Admits as Prior Art”, submitted Mar 2010.
Digital Island; “TraceWare White Paper;” Digital Island San Francisco, CA 64105 USA; Jun. 1999 (8 pp.).
Eastlake, “Domain Name System Security Extensions”, Internet Engineering Task Force, Request for Comments 2535, Mar. 1999.
Gargano et al., RFC: 1834, “Whois and Network Information Lookup Service,” Aug. 1995.
Harrenstien, “Nicname/Whois”, Internet Engineering Task Force, Request for Comments 954, Oct. 1985.
lmielinski, Tomasz, et al., “Geographic Addressing, Routing, and Resource Discovery with the Global Positioning System,” Computer Science Dept. Rutgers, The State University, Piscataway, NJ 08855; Oct. 19, 1996; pp. 1-10.
Kessler & Sheppard; “A primer on Internet and TCP/IP Tools and Utilities;” Network Working Group; Request for Comments: 2151; FYI: 30; Obsoletes: RFC 1739; Category: Informational; http:www.ietff.org/rfc/rfc2151.txt; Jun. 1997; (pp. 1-46).
Lambert, John; “Subnet Masking Definition;” www.exabyte.net/lambert/subnet/subnet—masking—definition.htm; 1999.
Lamm, Stephen E., et al., “Real Time Geographic Visualization of World Wide Web Traffic,” WWW Journal, Issue 3. “Undated Reference, Applicant Admits as Prior Art”, submitted Mar. 2010.
McCurley, Kevin S. “Geospacial Mapping and Navigation of the Web”; IBM Almaden Research Center; San Jose, CA 95120; May 1-5, 2001; pp. 221-229.
Narushige Shiode, “Analyzing the Geography of Internet Address Space” http://geog.ucl.uk/casa/martine/internetspace; pp. 1-3; “Undated Reference, Applicant Admits as Prior Art”, submitted Mar. 2010.
Roussea, Jean-Marc; Roy, Serge, “GeoRoute: An Interactive Graphics System for Routing and Scheduling Over Street Networks,” IEEE Sep. 1989; pp. 161-163.
Woolley, S, “We Know Where You Live”, Forbes Magazine, Nov. 13, 2000.
Digital Element, “NetAcuity Edge, A digital Element Product Sheet,” Jul. 28, 2009.
Digital Element, “NetAcuity Edge, A New ‘Edge’ for Global Online Targeting,” Jul. 28, 2009. Available at http://www.digitalelement.com/our—technology/edge.html.
Digital Element, “Digital Element Brings a New ‘Edge’ to Global Online Targeting,” Press Release of Jul. 28, 2009. Available at http://www.digitalelement.com/press—room/re—072809.html.
Carton, Sean, “Geotargeting: Why it Mattersto Marketers, ClickZ Today,” Apr. 7, 2003, 3 pages.
Digital Envoy, Technology Review, MIT's Magazine of Innovation, Names Sanjay Parekh One of the World's Top Young Innovators, Sep. 15, 2003 (2 pages).
MacVittie, Lori, “Coyote Point Emissary Uses Geolocating to Enhance Load-Balancing,” Network Computing, Mar. 18, 2002 (1 page).
Moore, et al, “Where in the World is netgeo.caida.org?,” Cooperative Association for Internet Data Analysis, Jul. 2000 (11 pages).
New Architect Magazine Review, Coyote Point Emissary, Nov. 2002 (1 page).
Parekh, Sanjay, “A Sensing of Place” found at http://www.e-insite.net/commvergemag/index.asp?layout=articlePrint Jun. 1, 2002, 4 pages.
Economist.Com Technology Quarterly, “The Revenge of Geography,” Mar. 13, 2003, 7 pages.
Related Publications (1)
Number Date Country
20110113116 A1 May 2011 US