WO2013144435A1

WO2013144435A1 - Method and apparatus for geo-coding unstructured address information

Info

Publication number: WO2013144435A1
Application number: PCT/FI2013/050319
Authority: WO
Inventors: Deepti Chafekar; Umesh Chandra; Kuldeep Yadav; Sneha SHUKLA; Deepak Prabhu DESAI
Original assignee: Nokia Corporation
Priority date: 2012-03-28
Filing date: 2013-03-21
Publication date: 2013-10-03

Abstract

An approach is provided for geo-coding unstructured address information. A geo-coding platform processes and/or facilitates a processing of one or more address records to determine one or more fields (303). The geo-coding platform then determines one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks (31 1 ). The geo-coding platform then determines to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields.

Description

METHOD AND APPARATUS FOR GEO-CODING UNSTRUCTURED ADDRESS

INFORMATION

BACKGROUND

[0001] Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling mobile services. One area of interest has been the development of mapping and location-based services that include geo-coded point of interest (POI) data that can be made available to users via a wide range of computing devices (e.g., mobile phones, personal computers, etc.). Geo-coding is the process of determining geographic coordinates (e.g., latitude-longitude coordinates) from other associated geographic data. Traditionally, geo-coding is resolved by using Global Positioning System (GPS) devices to record the geo-coordinates of one or more POIs. In addition, geo-coding can be resolved through address interpolation. In developed countries (e.g., the United States), addresses interpolation works because the addresses are often structured (e.g., street, city, state, and zip code) and street segments are usually attributed with address ranges. As a result, geo- coding a POI (e.g., a restaurant) can be accomplished by matching the address of the POI with a street and specific segment on a map in order to determine the approximate geographic location of the POI on the map. However, in growth economies (e.g., India, parts of Asia-Pacific, and Africa) addresses are often unstructured (i.e., do not adhere to any particular scheme) and/or are based on colloquial location information. Therefore traditional geo-coding algorithms in these regions are not particularly useful. Addresses in growth economies do, however, often include references to POIs, buildings, landmarks, or a combination thereof. Accordingly, service providers and device manufactures face significant technical challenges in geo-coding unstructured addresses and/or colloquial location information in growth economies.

SOME EXAMPLE EMBODIMENTS

[0002] Therefore, there is a need for an approach for geo-coding unstructured address information. [0003] According to one embodiment, a method comprises processing and/or facilitating a processing of one or more address records to determine one or more fields. The method also comprises determining one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks. The method further comprises determining to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields.

[0004] According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code for one or more computer programs, the at least one memory and the computer program code configured to, with the at least one processor, cause, at least in part, the apparatus to process and/or facilitate a processing of one or more address records to determine one or more fields. The apparatus is also caused to determine one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks. The apparatus is further caused to determine to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields.

[0005] According to another embodiment, a computer-readable storage medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause, at least in part, an apparatus to process and/or facilitate a processing of one or more address records to determine one or more fields. The apparatus is also caused to determine one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks. The apparatus is further caused to determine to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields.

[0006] According to another embodiment, an apparatus comprises means for processing and/or facilitating a processing of one or more address records to determine one or more fields. The apparatus also comprises means for determining one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks. The apparatus further comprises means for determining to geo-code the one or more address records based, at least in part, on a geo- coding of the one or more landmarks identified in the at least one of the one or more fields.

[0007] In addition, for various example embodiments of the invention, the following is applicable: a method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on (or derived at least in part from) any one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.

[0008] For various example embodiments of the invention, the following is also applicable: a method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform any one or any combination of network or service provider methods (or processes) disclosed in this application.

[0009] For various example embodiments of the invention, the following is also applicable: a method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on data and/or information resulting from one or any combination of methods or processes disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.

[0010] For various example embodiments of the invention, the following is also applicable: a method comprising creating and/or modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based at least in part on data and/or information resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention. [0011] In various example embodiments, the methods (or processes) can be accomplished on the service provider side or on the mobile device side or in any shared way between service provider and mobile device with actions being performed on both sides.

[0012] For various example embodiments, the following is applicable: An apparatus comprising means for performing the method of any of originally filed claims 1-20 and 36- 38.

[0013] Still other aspects, features, and advantages of the invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the invention. The invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings:

[0015] FIG. 1 is a diagram of a system capable of geo-coding unstructured address information, according to one embodiment; [0016] FIG. 2 is a diagram of the components of geo-coding platform, according to one embodiment;

[0017] FIGs. 3 and 4 are flowcharts of a process for geo-coding unstructured address information, according to one embodiment;

[0018] FIG. 5 is a diagram of a graph utilized in the processes of FIG. 4, according to various embodiments;

[0019] FIG. 6 is a diagram of hardware that can be used to implement an embodiment of the invention;

[0020] FIG. 7 is a diagram of a chip set that can be used to implement an embodiment of the invention; and [0021] FIG. 8 is a diagram of a mobile terminal (e.g., handset) that can be used to implement an embodiment of the invention.

DESCRIPTION OF SOME EMBODIMENTS

[0022] Examples of a method, apparatus, and computer program for geo-coding unstructured address information are disclosed. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention.

[0023] As used herein, the term "point of interest", or POI, refers to a specific point location that an individual entity, business entity, or any legal entity may find useful or interesting. This term is used interchangeable with landmark. A POI may be a historical monument, cinema theatre, pub, bar, restaurant, hotel, club, venue, sightseeing spot, shopping mall/center, building, museum, industrial/science park, police/fire station, post office, bank, ATM machine, hospital, pharmacy, school, church, temple, golf course, bridge, historic house, camping/caravan site, daycare center, community center, tunnel, airport, roadway, waterway, railway, rock formation, spring, oasis, mountain, etc.

[0024] FIG. 1 is a diagram of a system capable of geo-coding unstructured address information, according to one embodiment. As previously discussed, one area of interest has been the development of mapping and location-based services that include geo-coded point of interest (POI) data that can be made available to users via a wide range of computing devices (e.g., mobile phones, personal computers, etc.). Further, geo-coding is the process of determining geographic coordinates (e.g., latitude-longitude coordinates) from other associated geographic data. Traditionally, geo-coding is resolved through address interpolation. In developed countries (e.g., the United States) address interpolation is useful because the addresses are structured (e.g., street, city, state, and zip code) and street segments are usually attributed with address ranges. As a result, geo-coding a POI (e.g., a restaurant) can be accomplished by matching the address of the POI with a street and a specific segment of a map in order to determine the approximate geographic location of the POI on the map. However, addresses in growth economies (e.g., India, parts of Asia-Pacific, and Africa) often do not adhere to any particular structure or scheme thereby making it difficult to deploy traditional geo-coding schemes. By way of example, the following two address records are taken from Bangalore and New Delhi in India, respectively:

• McDonald's Family Restaurant, Survey No. 10, Near Infinity Tech Park, Opp to Big Baazar, Benaganahalli, Old Madras Road, Krishnarajapuram, Bangalore

• Winsome World, E- 16/1260, NR Gurudwara Khalsa, next to Sabzi Mandi Chowk, Tank Road, Karol Bagh, Delhi.

[0025] As the above two examples demonstrate, address records in growth economies are often unstructured and/or may contain imprecise landmark references (e.g., "Infinity Tech Park" or "Big Baazar"). In addition, address records in growth economies may contain colloquial references and/or abbreviations that may be different from their official names. Further, these addresses may contain references to an area name, which may not have official geo -boundaries. Last, address schemes and notions in growth economies may differ from one city to another based on the nature language that is prevalent in that given city. By way of example, the word "chowk" in native language means a "town square." This reference word, however, is mostly limited to addresses in the northern and western parts of India.

[0026] In contrast, if service providers and device manufactures were able to determine the geo-coordinates of a particular landmark (e.g., "Infinity Tech Park") from one or more databases then the McDonald's Family Restaurant address could also be geo-coded by matching "Infinity Tech Park" from the address records to the corresponding geo- coordinates in the database. However, determining which terms in the address records are, in fact, the landmark is not an easy task. This is largely due to the unstructured nature of address records in growth economies. Moreover, in growth economies there are several landmarks that can be anything such as "mom and pop" stores, apartment buildings, malls, multiplexes, etc. It is therefore not feasible to determine the geo-coordinates for all of these landmarks.

[0027] To address this problem, a system 100 of FIG. 1 introduces the capability to geo-code unstructured address information. In one embodiment, the system 100 first determines one or more address records from one or more databases provided by one or more third parties (e.g., YAHOO, NAVTEQ, etc.) to determine one or more key or popular landmarks. In one embodiment, the system 100 may also determine the one or more address records from one or more user generated queries (e.g., a user searching for a local restaurant). In another embodiment, the system 100 may determine the one or more address records utilizing various crowd sourcing techniques (e.g., requesting users to input two or three landmarks from their area of residence or work).

[0028] In one embodiment, once the system 100 determines the one or more address records, the system 100 parses the one or more address records utilizing various heuristic techniques to determine one or more fields or components of the one or more address records. In one embodiment, the system 100 determines at least one sequence for parsing the one or more fields based on a geographical area associated with the one or more address records (e.g., India). In this example use case, the system 100 next determines that the one or more fields relate to one or more landmarks, one or more streets, a particular area, and a particular city. In one embodiment, although the one or more address records may be unstructured, the system 100 still determines based on research that the first field often identifies a POI name (e.g., a building) and the last field often identifies a city name. By way of example, the system 100 may determine to parse the following addresses:

• Maharaja Furniture, No. 19/1, Opp to Cisco Building, Next To Aircent Software, Outer Ring Road, Marathahalli, Bangalore · Winsome Building E- 16/1260, NR Gurudwara Khalsa, next to Sabzi Mandi

Chowk, Tank Road, Karol Bagh, Delhi

[0029] In one embodiment, the system 100 first parses the city information from the one or more address records. As previously stated, the city information in this geographic region (e.g., India) is often located at the end of the address records and is sometimes followed by a zip code. In the instance where a zip code is included in one or more address records, the system 100 first removes the numbers from the address record. In one embodiment, the system 100 then determines to assign the last couple of words in the address record a label or tag related to a "city name" and then compares these words against one or more databases of city names in a given country (e.g., India). It is contemplated that one or more string matching techniques may be employed by the system 100 to determine whether the city name in the address record matches a city name in one or more databases.

[0030] In one embodiment, once the system 100 determines the city name from the closest matching city in the one or more databases, the system 100 removes the city name from the address record to then determine the area name. It is further contemplated that in this particular geographic region an area name often occurs at the tail end of the address record (e.g., the last 15% of the record). Accordingly, in one embodiment, the system 100 determines to assign a label or tag related to an "area name" to the tail end of the one or more address records and then compares these words against one or more databases of area names in a given country (e.g., India). Again, it is contemplated that one or more string matching techniques may be employed by the system 100 to determine whether the area name in the address record matches an area name in one or more databases. By way of example, the system 100 is able to determine that Delhi is the city name in the address "Winsome Building E- 16/1260, NR Gurudwara Khalsa, next to Sabzi Mandi Chowk, Tank Road, Karol Bagh, Delhi" based on the one or more city name databases. Therefore, the system 100 next determines whether "Karol Bagh" is an area name that also matches an area name in one or more databases.

[0031] In one embodiment, the system 100 next determines one or more landmarks from the one or more address records. It is contemplated that the one or more address records will often be separated by one or more delimiters (e.g., commas, semicolons, new line characters, etc.). By way of example, the system 100 splits the address "Winsome Building E- 16/1260, NR Gurudwara Khalsa, next to Sabzi Mandi Chowk, Tank Road, Karol Bagh, Delhi" into the following seven fields: (i) Winsome Building E-16/1260, (ii) NR Gurudwara Khalsa, (iii) next to Sabzi Mandi Chowk, (iv) Tank Road, (v) Karol Bagh, and (vii) Delhi. It is also contemplated that in an example use case where the one or more addresses do not contain one or more delimiters, the system 100 could still apply a similar organizational logic in order to parse the one or more address records into one or more fields or components. As previously discussed, it is contemplated that the first field of the comma-separated address record often relates to a business name, a building name, a POI, or a combination thereof. In this example use case, the system 100 first removes the numbers "E- 16/1260" and then allocates the field "Winsome Building" to the POI name field.

[0032] In one embodiment, the system 100 can attempt to match "Winsome Building" against one or more databases containing geo-coded landmarks in a given country or region (e.g., India). If the system 100 determines a match, the system 100 can determine to geo- code the address record related to the POI and proceed to parse and/or geo-code one or more other address records.

[0033] In one embodiment, in the likely instance where the system 100 is unable to match the POI name field with one or more landmark databases, the system 100 proceeds to determine one or more scores for the field "Winsome Building" based on one or more probabilities that the field specifies one or more landmarks. In one embodiment, the system 100 determines the one or more scores, the one or more probabilities, or a combination thereof based on a comparison of the one or more fields with one or more keywords stored in one or more databases. More specifically, the one or more databases include one or more prepositions that are indicative of one or more landmarks such as "near," "next to," "opposite," etc. and may also include common abbreviations (e.g., "NR" for near or "Opp" for opposite). A match by the system 100 of the one or more values of the one or more fields with one or more of the prepositions in the one or more databases is a strong indicator that the associated field is a landmark field. By way of example, in the address "Maharaja Furniture, No. 19/1, Opp to Cisco Building, Next To Aircent Software, Outer Ring Road, Marathahalli, Bangalore" the system 100 can determine that because the prepositional phrase "Opp to" (i.e., Opposite to) in the field "Opp to Cisco Building" matches one or more prepositional phrases in the one or more databases there is a high probability that the field "Cisco Building" relates to a landmark. As previously discussed, if the system 100 is able to match "Cisco Building" with a geo-coded landmark in one or more databases, the system 100 can geo-code this address record and proceed to parse and/or geo-code one or more other address records. [0034] In one embodiment, where the one or more address records do not contain one or more prepositions and/or prepositions that are indicative of one or more landmarks, the system 100 may determine whether the one or more address records contain one or more reference keywords that are characteristic of one or more local or regional words for describing one or more landmarks. By way of example, the one or more reference keywords in the one or more databases may include words such as "building," "apartment," "station," "complex," "bank," "center," "colony," "showroom," "temple," "bar," "plaza," "hospital," "furniture," etc. as well as popular abbreviations such as "bldg.," "apt.," "clny.," etc. In addition, the one or more databases may also include certain reference keywords that make more sense in one city as opposed to another (e.g., "layout" is mostly found in Bangalore and some southern cities in India) and/or one or more reference keywords that are native to a particular city or area (e.g., "bagh" which means garden). A match by the system 100 of the one or more values of the one or more fields with the one or more reference keywords in the one or more databases is a good indicator that the one or more fields associated with the one or more reference keywords is a landmark field. The potential complexity of reference keywords, particularly in growth economies, highlights the importance of the system 100 first identifying the city or area name with respect to one or more address records in order to maximize computational resources.

[0035] In one embodiment, the system 100 next determines to specify one or more confidence levels for respective ones of the one or more keywords, wherein the one or more confidence levels are used to weight the comparison of the respective ones of the one or more keywords to determine the one or more scores, the one or more probabilities, or a combination thereof. By way of example, the system 100 may assign a higher confidence level to a keyword such as "temple" compared to a keyword such as "furniture," which may or may not reference a building that is well-known in a given area (i.e., a landmark). By way of another example, the system 100 may assign a higher confidence level to a native keyword such as "bagh" (which means garden) compared to a native keyword such as "nagar" (which means a small area).

[0036] In one embodiment, once the system 100 determines the one or more scores for a particular field, the system 100 combines the scores and assigns an overall score for each of the comma-separated fields. The system 100 then determines whether the one or more fields is associated with an overall score above a certain threshold and, if so, the system 100 determines the one or more fields relate to one or more landmarks.

[0037] In one embodiment, once the system 100 determines one or more landmark fields in the one or more address records, the system 100 removes the landmark fields from the one or more address records in order to determine the one or more streets referenced in the one or more address records. More specifically, the system 100 parses the one or more fields related to streets by determining one or more keywords referenced in the one or more address records relates to one or more keywords related to street in one or more databases. By way of example, such keywords may include "street," "road," "drive," "lane," "path," "highway," "parking," "route," "subway," etc. In addition, the system 100 can determine whether one or more abbreviations (e.g., "st." or "rd.") are included in one or more address records and whether one or more native keywords (e.g., "gali" or "marg") are also included in the one or more address records. As a result, if the system 100 determines that one or more keywords referenced in the one of the address records relates to streets, then the system 100 can determine with confidence that the one or more fields is a street name.

[0038] In one embodiment, after the system 100 determines the one or more landmarks referenced in the one or more address records, the system 100 next determines which one of the one or more landmarks to geo-code and/or to assign for later geo-coding (e.g., by manual geo-coding). As previously discussed, it is not feasible to geo-code all of the landmarks identified in the one or more address records obtained from the one or more databases, one or more user queries, and/or one or more crowd sourcing techniques. In addition to the large number of landmarks in growth economies, geo-coded data is usually collected by a manual process (e.g., one or more users utilizing mobile devices to collect the geo-codes and other location-based information about a landmark or POI). Therefore, it is contemplated that once the system 100 determines the one or more landmarks among the one or more address records, the system 100 can determine the one or more most referenced landmarks to be geo-coded through a manual process or interpolation based on other geo-coded landmarks. Further, the system 100 can then utilize the geo-codes of these one or more reference landmarks to geo-code numerous other address records. [0039] In one embodiment, the system 100 determines the one or more key or important landmarks by determining frequency information, popularity information, or a combination thereof related to the one or more reference landmarks. The system 100 is able to determine this information in a number of ways. In one embodiment, the system 100 generates one or more bins (e.g., a column in a dataset) for the one or more landmarks referenced in the one or more address records related to a particular area. In one example use case, the system 100 first determines the one or more landmarks referenced in the address record "ADDR1," "The Urban Nawaab, 4^th Floor, Below Roomali with a View, Opp Innovative Multiplex, Outer Ring Road, Marathahalli, Bangalore." Based on the parsing system method discussed above, the system 100 generates bins for the landmarks "Urban Nawaab," "Roomali with a View," and "Innovative Multiplex" for the area "Marathahalli" and the address "ADDR1" is added by the system 100 to each of the bins. The system 100 next determines the one or more landmarks referenced in the address record "ADDR2," "Aspirations, 90/2, 2^nd Floor, Opposite Innovative Multiplex, Above Next Electronics, Marathahalli, Bangalore." Again, based on the parsing method previously discussed, the system 100 generates bins for the landmarks "Aspirations" and "Next Electronics" for the area "Marathahalli" and the address "ADDR2" is added by the system 100 to each of the bins as well as the bin related to "Innovative Multiplex." Consequently, the bin related to "Innovative Multiplex" contains both address records "ADDRl" and "ADDR2." The system 100 is then able to determine based on the number of address records in each bin which one of the one or more landmarks are the most referenced landmarks and these landmarks are then designated by the system 100 as the key landmarks for the area.

[0040] In addition to determining which one or more landmarks are the key landmarks for a given area, in one embodiment, the system 100 can also determine the number of POIs, landmarks, or a combination thereof that can also be geo-coded based on the geo- coding of the one or more key landmarks. More specifically, the system 100 determines one or more landmark references between at least one of the one or more address records and at least another one of the one or more address records. In one example use case, the system 100 graphically determines the relationship between the one or more landmark references. In particular, the system 100 determines to generate a graph depicting (a) the one or more reference landmarks as one or more nodes of the at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes. The system 100 can then determine the frequency information, the popularity information, or a combination thereof based on the number of the one or more edges associated with the one or more nodes. By way of example, based on the two example addresses described above, "ADDR1" and "ADDR2," the system 100 can determine that the landmark "Innovative Multiplex" is a reference landmark constituting a node with two edges to the landmark references "Urban Nawaab," and "Aspiration." Based on this determination, it is apparent that by determining the geo-code for "Innovative Multiplex," the system 100 can also approximate the geo-codes for the four other landmarks referenced in address records "ADDR1" and "ADDR2." An illustrative example of this graph is depicted in FIG. 5.

[0041] As shown in FIG. 1, the system 100 comprises one or more user equipment (UE) lOla-lOlm (also collectively referred to as UEs 101) having connectivity to a geo- coding platform 103 via a communication network 105. The location information may be utilized by applications 107a-107m of the UEs 101 (e.g., location-based applications) (also collectively referred to as applications 107). The geo-coding platform 103 is also associated with one or more location databases 109a-109n (also collectively referred to as location databases 109) that can hold multiple tables or object stores. In one embodiment, the one or more location databases 109 may also contain one or more lists of cities, areas, POIs, one or more geo-codes related to the POIs, one or more prepositions that are indicative of one or more landmarks, and one or more reference keywords associated with landmarks and/or streets including native and/or colloquial keywords for one or more growth economies (e.g., India). It is contemplated that the location databases 109 may exist independently or within a cloud computing and/or cloud storage platform.

[0042] In one embodiment, the geo-coding platform 103 also has connectivity to a service platform 111 containing one or more services 113a-113p (e.g., mapping and location-based services, POI data services, etc.) (also collectively referred to as services 113) via the communication network 105. The geo-coding platform 103 and the service platform 11 1 may also have connectivity to one or more content providers 115a-l 15q (e.g., third-party POI and/or geo-coding data providers, public databases, etc.) via the communication network 105. In certain embodiments, the services 115 may also have connectivity to the applications 107 in order to facilitate local search functions, mapping and route guidance, and/or to obtain one or more address records from one or more queries (e.g., a local search for "Coconut Grove Restaurant, Marathahalli) and/or one or more crowd sourcing techniques (e.g., requesting users to input two or three landmarks from their area of residence or work).

[0043] In one embodiment, the UEs 101 may utilize location-based technologies GPS receivers, cellular triangulation, assisted-GPS (A-GPS), etc.) to manually provision the geo- coding platform 103 and/or the services 113 with geo-coordinates relative to one or more key landmarks. For instance, the UE 101 may include a GPS receiver to obtain geographic coordinates from satellites 117 to determine the current location associated with the UE 101, which can then be provisioned to the geo-coding platform 103 and/or the services 113 for geo-coding of one or more landmarks on one or more maps. [0044] By way of example, the communication network 105 of system 100 includes one or more networks such as a data network, a wireless network, a telephony network, or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), a public data network (e.g., the Internet), short range wireless network, or any other suitable packet- switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fiber-optic network, and the like, or any combination thereof. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., worldwide interoperability for microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), wireless LAN (WLAN), Bluetooth®, Internet Protocol (IP) data casting, satellite, mobile ad-hoc network (MANET), and the like, or any combination thereof.

[0045] The UE 101 is any type of mobile terminal, fixed terminal, or portable terminal including a mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the UE 101 can support any type of interface to the user (such as "wearable" circuitry, etc.). [0046] In certain embodiments, the geo-coding platform 103 first determines one or more address records from one or more stores provided by one or more services 113 (e.g., YAHOO, NAVTEQ, etc.), one or more content providers 115, or a combination thereof to determine one or more reference landmarks (e.g., key landmarks) in a given area. The geo- coding platform 103 may also obtain the one or more stores of address records from one or more applications 107 of one or more UEs 101 (e.g., through local search applications) and/or as part of one or more crowd sourcing techniques (e.g., requesting users to input two or three landmarks from their area of residence or work).

[0047] In one embodiment, the geo-coding platform 103 next parses the one or more address records utilizing various heuristic techniques to determine one or more fields or components of the one or more address records. In one embodiment, the geo-coding platform 103 determines at least one sequence for parsing the one or more fields based on a geographical area associated with the one or more address records (e.g., India). In this example use case, the geo-coding platform 103 determines that the one or more fields relate to one or more landmarks, one or more streets, a particular area, and/or a particular city. [0048] In one embodiment, the geo-coding platform 103 first parses the city information from the one or more address records. As previously discussed, the city information in this geographic region (e.g., India) is often located at the end of the address record. As a result, the geo-coding platform 103 determines to assign the last couple of words in the address record a label or tag related to a "city name" and then compares these words against city names contained in the location databases 109. Once the geo-coding platform 103 determines the city name from the closet matching city in the one or more location databases 109, the geo-coding platform 103 removes the city name from the address record to determine the area name. Similar to the location of the city name in address records in this region, the area name also often occurs at the tail end of the address records (e.g., the last 15% of the record). As a result, the geo-coding platform 103 determines to assign a label or tag related to an "area name" to the tail end of the one or more address records and then compares these words against area names contained in the location databases 109.

[0049] In certain embodiments, once the geo-coding platform 103 determines the city and area related to one or more address records, the geo-coding platform 103 determines one or more landmarks referenced in the one or more address records. As previously discussed, the one or more address records will often be separated by one or more delimiters (e.g., commas, semicolons, new line characters, etc.). Moreover, the first field of the delimited address record often relates to a business name, a building, a POI, or a combination thereof. As a result, the geo-coding platform 103 can allocate the first field of one or more address records to the POI name field and then assign this field a landmark probability score based on one or more probabilities that the one or more fields pertain to one or more landmarks. In certain embodiments, the geo-coding platform 103 can attempt to match the POI identified in the first field with one or more POIs contained in the location databases 109. If the geo-coding platform 103 determines a match, the geo-coding platform 103 can geo-code the address record related to the POI and proceed to parse and/or geo-code one or more other address records.

[0050] In the likely instance where the geo-coding platform 103 is unable to match the POI name field with one or more landmarks contained in the location databases 109, the geo-coding 103 platform proceeds to determine one or more scores for the one or more fields based on one or more probabilities that the one or more fields specify one or more landmarks. In particular, the geo-coding platform 103 causes a comparison of the one or more values of the one or more fields to one or more keywords associated with one or more landmarks. The one or more keywords can include one or more prepositions that are indicative of one or more landmarks, one or more reference keywords that are characteristic of one or more local or regional words for describing one or more landmarks, or a combination thereof. More specifically, the geo-coding platform 103 compares any prepositions referenced in the address record against one or more prepositions in the location databases 109 (e.g., "near," "next to," "opposite," etc.). As previously discussed, the presence of one or more these prepositions in the one or more address records is a strong indicator that the associated field is a landmark field. [0051] In certain embodiments, where the one or more address records do not contain one or more prepositions and/or prepositions that are indicative of one or more landmarks, the geo-coding platform 103 can also determine whether one or more reference keywords are contained in the one or more address records and match one or more reference keywords and/or short form abbreviations contained in the location databases 109. As previously discussed, the location databases 109 may also include native and/or colloquial keywords. Again, the presence of any of these reference keywords in the one or more address records is a good indicator that the one or more fields associated with the one or more keywords is a landmark field. [0052] In one embodiment, the geo-coding platform 103 next determines to specify one or more confidence levels for respective ones of the one or more keywords, wherein the one or more confidence levels are used to weight the comparison of the respective ones of the one or more keywords to determine the one or more scores. By way of example, the geo- coding platform 103 may assign a higher confidence level to a keyword such as "temple" compared to a keyword such as "furniture," which may or may not reference a building that is well-known in a given area (i.e., a landmark). By way of another example, the geo- coding platform 103 may assign a higher confidence level to a native keyword such as "bagh" (which means garden) compared to a native keyword such as "nagar" (which means a small area). [0053] In one embodiment, once the geo-platform 103 has determined the one or more scores for each field, the geo-platform 103 combines the scores and assigns an overall score for each of the delimited fields. The geo-coding platform 103 then determines whether the one or more fields is associated with an overall score above a certain threshold and, if so, the geo-coding platform 103 determines the one or more fields relate to one or more landmarks.

[0054] In certain embodiments, once the geo-coding platform 103 determines the one or more landmarks in the one or more address records, the geo-coding platform 103 removes the one or more landmarks from the one or more address records in order to determine the one or more streets referenced in the one or more address records. In one embodiment, the geo-coding platform 103 parses the one or more fields related to streets by determining one or more keywords referenced in the one or more address records match one or more keywords related to streets in the location databases 109. By way of example, if the geo-coding platform 103 determines that one or more keywords related to streets is referenced in the one or more address records, then the geo-coding platform 103 can determine with confidence that the one or more fields is a street name. [0055] In one embodiment, after the geo-coding platform 103 determines the one or more landmarks referenced in the one or more address records, the geo-coding platform 103 next determines which one of the one or more landmarks to geo-code and/or to assign for later geo-coding (e.g., by manual geo-coding). More specifically, the geo-coding platform 103 determines which one of the one or more landmarks is the most referenced landmark (i.e., key landmark) among the one or more address records and then determines to geo-code these landmarks through either a manual process or interpolation based on other geo-coded landmarks. In certain embodiments, the geo-coding platform 103 can then utilize the geo-codes of these one or more reference landmarks in order to geo-code numerous other address records. [0056] In certain embodiments, the geo-coding platform 103 determines the one or more key landmarks by determining frequency information, popularity information, or a combination thereof related to the one or more reference landmarks. The geo-coding platform 103 is able to determine this information in a number of ways. In one embodiment, the geo-coding platform 103 generates one or more bins (e.g., a column in a dataset) in the location databases 109 for the one or more landmarks referenced in the one or more address records related to a particular area. More specifically, any address that references a landmark "X" in an area "A" gets added by the geo-coding platform 103 to the bin of landmark "X" for area "A". The geo-coding platform 103 can then determine at the end of the process that the bins with the most addresses are the most referenced landmarks in a given area and are therefore prime candidates for geo-coding. Optionally, in certain embodiments, the geo-coding platform 103 can determine the frequency information, the popularity information, or a combination thereof relative to one or more reference landmarks by generating a graph of the relationship between the one or more landmarks. In addition, to determining the frequency information, the popularity information, or a combination thereof, the geo-coding platform 103 can also determine how many other POIs, landmarks, or a combination that can also be geo-coded based on the geo-coding of the one or more highly referenced landmarks. More specifically, the geo-coding platform 103 generates a graph that depicts (a) the one or more reference landmarks as one or more nodes of the at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes. The geo-coding platform 103 can then determine the frequency information, the popularity information, or a combination thereof as well as the geo-coding potential based on the number of the one or more edges associated with the one or more nodes.

[0057] By way of example, the UEs 101, the geo-coding platform 103, the applications 107, the service platform 111, and the content providers 115 communicate with each other and other components of the communication network 105 using well known, new or still developing protocols. In this context, a protocol includes a set of rules defining how the network nodes within the communication network 105 interact with each other based on information sent over the communication links. The protocols are effective at different layers of operation within each node, from generating and receiving physical signals of various types, to selecting a link for transferring those signals, to the format of information indicated by those signals, to identifying which software application executing on a computer system sends or receives the information. The conceptually different layers of protocols for exchanging information over a network are described in the Open Systems Interconnection (OSI) Reference Model. [0058] Communications between the network nodes are typically effected by exchanging discrete packets of data. Each packet typically comprises (1) header information associated with a particular protocol, and (2) payload information that follows the header information and contains information that may be processed independently of that particular protocol. In some protocols, the packet includes (3) trailer information following the payload and indicating the end of the payload information. The header includes information such as the source of the packet, its destination, the length of the payload, and other properties used by the protocol. Often, the data in the payload for the particular protocol includes a header and payload for a different protocol associated with a different, higher layer of the OSI Reference Model. The header for a particular protocol typically indicates a type for the next protocol contained in its payload. The higher layer protocol is said to be encapsulated in the lower layer protocol. The headers included in a packet traversing multiple heterogeneous networks, such as the Internet, typically include a physical (layer 1) header, a data- link (layer 2) header, an internetwork (layer 3) header and a transport (layer 4) header, and various application (layer 5, layer 6 and layer 7) headers as defined by the OSI Reference Model. [0059] FIG. 2 is a diagram of the components of a geo-coding platform, according to one embodiment. By way of example, the geo-coding platform 103 includes one or more components for geo-coding unstructured address information in emerging economies. It is contemplated that the functions of these components may be combined in one or more components or performed by other components of equivalent functionality. In one embodiment, the geo-coding platform 103 includes a control logic 201, a communication module 203, a parsing module 205, an analysis module 207, and a storage module 209.

[0060] The control logic 201 oversees tasks, including tasks performed by the communication module 203, the parsing module 205, the analysis module 207, and the storage module 209. For example, although the other modules may perform the actual task, the control logic 201 may determine when and how those tasks are performed or otherwise direct the other modules to perform the task.

[0061] The communication module 203 is used for communication between the UEs 101, the geo-coding platform 103, the service platform 111 , the content providers 115, and satellites 117. The communication module 203 also may be used to communicate commands, requests, data, etc. The communication module 203, in connection with the storage module 209, may also be used to cause a transfer of one or more reference address records from one or more databases. More specifically, the one or more databases may include one or more public address stores (e.g., provided by one or more third-party providers and/or services), one or more query input stores (e.g., user local search queries), one or more crowdsourced address stores (e.g., two or three landmarks inputted by a user upon request from his or her area of residence or work), or a combination thereof. The communication module 203, in connection with the analysis module 207, may also be used to compare a city name, an area name, one or more prepositions, one or more reference keywords contained in one or more address records against one or more lists of related terms in one or more databases (e.g., the location databases 109). The communication module 203 also may be used to create at least one graph depicting (a) the one or more reference landmarks as one or more nodes of at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes. Further, the communication module 203 may also be used to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the one or more address records.

[0062] The parsing module 205 is used for processing and/or facilitating a processing of one or more unstructured address records from one or more stores to determine the one or more fields or components within the one or more address records. The parsing module 205, in connection with the analysis module 207, may also be used to determine that the one or more fields relate to one or more streets, an area, a city, a region, or a combination thereof. In one example use case, the parsing module 205, in connection with the analysis module 207, may be used to determine at least one sequence for parsing the one or more fields based, at least in part, on a geographic area (e.g., India) associated with the one or more address records. The parsing module 205 may then be used to cause a parsing of the one or more address records according to the at least one sequence to determine the one or more fields. By way of example, the parsing module 205 may be used to parse the following address records:

Chowk, Tank Road, Karol Bagh, Delhi

Although these example address records may be unstructured, there are still some hints in the one or more address records that can be exploited by the parsing module 205 in order to determine the one or more fields. More specifically, the parsing module 205 can assume that the first field of one or more address records often references a POI name (e.g., "Maharaja Furniture" or "Winsome Building") and the last field often references a city name (e.g., "Bangalore" or "Delhi"). In addition, the parsing module 205 can assume that the one or more address records is delimited (e.g., includes commas, semicolons, new line characters, etc.). [0063] In one embodiment, the parsing module 205 first parses the city name from the one or more address records. As previously discussed, the city information in this geographic region (e.g., India) is often located at the end of the one or more address records and is sometimes followed by a zip code. In the instance where a zip code is included in the one or more address records, the parsing module 205 first removes the numbers from the address. The parsing module 205 may then be used to assign the last couple of words in the one or more address records a label or tag related to a "city name" and then, in connection with the analysis module 207, compare these words against one or more databases of city names in a given country (e.g., the location databases 109). [0064] In one embodiment, once the parsing module 205, in connection with the analysis module 207, determines the city name from the closest city name in the one or more databases, the parsing module 205 removes the city name from the address record to then determine the area name. In one embodiment, the parsing module 205, in connection with the communication module 203 and the storage module 209, can temporarily store the city name in the location databases 109. As previously discussed, the area information in this geographic region (e.g., India) often occurs at the tail end of the address records (e.g., the last 15% of the record). Accordingly, the parsing module 205 determines to assign a label or tag related to an "area name" to the tail end of the one or more address records and then, in connection with the analysis module 207, compares these words against one or more databases of area names in a given country (e.g., the parsing database 109). Similar to the city name, once the parsing module 205 and the analysis module 207 match the area name, the parsing module 205, in connection with the storage module 209, removes the area name and temporarily stores the information in the location databases 109.

[0065] In one embodiment, the parsing module 205 next determines one or more landmarks from the one or more address records. As previously discussed, the first field of a delimited address record often references a business name, a building, a POI, or a combination thereof in this particular geographic region. Therefore, the parsing module 205 can be used to remove any numbers from the first field and then allocate the field to the POI field name. In addition, the parsing module 205 can be used, in connection with the analysis module 207, to assign this field one or more scores based on one or more probabilities that the one or more terms in the field specify one or more landmarks. [0066] In certain embodiments, the parsing module 205, in connection with the analysis module 207, may also be used to determine whether one or more prepositions are referenced in the one or more address records and whether they can then be matched by the analysis module 207 against one or more prepositions in one or more that are indicative of one or more landmarks (e.g., "near," "next to," "opposite," etc.) in a given country (e.g., India). As previously discussed, the presence of one or more of these prepositions in the one or more address records is a strong indicator that the associated field is a landmark field. By way of example, in the address record "Maharaja Furniture, No. 19/1, Opp to Cisco Building, Next To Aircent Software, Outer Ring Road, Marathahalli, Bangalore" the parsing module 205, in connection with the analysis module 207, can parse the address record to determine that the prepositional phrase "Opp to" (i.e., Opposite to) in the field "Opp to Cisco Building" is indicative of a high probability that the field "Cisco Building" relates to a landmark.

[0067] In certain embodiments, the parsing module 205 may also be used to parse one or more street names from one or more address records. More specifically, the parsing module 205, in connection with the analysis module 207, parses the one or more fields related to streets by determining whether one or more keywords matches one or more keywords related to streets in one or more databases (e.g., the location databases 109).

[0068] The analysis module 207 is used to determine whether one or more fields of one or more address records relate one or more streets, an area, a city, a region, or a combination thereof by matching the names of the one or more referenced elements (e.g., a city) against the names of related elements in in one or more databases (e.g., the location databases 109). More specifically, the analysis module 207 utilizes the label or tags assigned by the parsing module 205 to prevent attempts to match one or more elements (e.g., a city) against a list of one or more disparate elements (e.g., a landmark). As previously discussed, the analysis module 207 may also be used to determine at least one sequence for parsing the one or more fields based, at least in part, on a geographical area (e.g., India) associated with the one or more address records. As also discussed, the analysis module 207, in connection with the parsing module 205, is used to compare the city name and/or the area name referenced in the one or more address records against city names and/or area names for a given country in one or more databases (e.g., the location databases 109). It is contemplated that the analysis module 207 can employ one or more string matching techniques in order to determine whether a city name and/or an area name matches a city name and/or an area name in the one or more databases.

[0069] The analysis module 207 is also used, in connection with the parsing module 205, to compare the one or more landmarks parsed from one or more address records against one or more databases of geo-coded landmarks in a given country (e.g., India). If the analysis module 207 determines a match, the analysis module 207, in connection with the communication module 203, can determine to geo-code the address record related to the landmark. If, however, the analysis module 207 fails to determine a match, the analysis module 207 is then used, in connection with the parsing module 205, to determine one or more scores, one or more probabilities, or a combination thereof that a particular field specifies one or more landmarks. In one embodiment, the analysis module 207 first compares the one or more fields with one or more keywords stored in the one or more databases (e.g., the location databases 109). The one or more databases may include one or more prepositions that are indicative of one or more landmarks (e.g., "near," "next to," "opposite," etc.), one or more reference keywords that are characteristic of one or more local or regional words for describing one or more landmarks, or a combination thereof. By way of example, the one or more reference keywords in the one or more databases may include keywords such as "building," "apartment," "station," "complex," "bank," "center," "colony," "showroom," "temple," "bar," "plaza," "hospital," "furniture," etc. as well as popular abbreviations such as "bldg.," "apt.," "clny.," etc. In addition, the one or more databases may also include certain reference keywords that make more sense in one city as opposed to another (e.g., "layout" is mostly found in Bangalore and some southern cities in India) and/or one or more reference keywords that are native to a particular city or area (e.g., "bagh" which means garden). In addition to comparing the keywords, the analysis module 207 may also be used to determine to specify one or more confidence levels for respective ones of the one or more keywords, wherein the one or more confidence levels are used to weight the comparison of the respective ones of the one or more keywords to determine the one or more scores. By way of example, the analysis module 207 may assign a higher confidence level to a keyword such as "temple" compared to a keyword such as "furniture," which may or may not reference a building that is well-known in a given area (i.e., a landmark). By way of another example, the analysis module 207 may assign a higher confidence level to a native keyword such as "bagh" (which means garden) compared to a native keyword such as "nagar" (which means a small area).

[0070] In one embodiment, the analysis module 207 is also used to determine the key or important landmarks in a given area by determining frequency information, popularity information, or a combination thereof related to the one or more landmarks. The analysis module 207 is able to determine this information in a number of ways. In one embodiment, the analysis module 207 causes, at least in part, a generation of one or more bins (e.g., a column in a dataset) in the location databases 109 for the one or more landmarks referenced in the one or more address records related to a particular area. More specifically, any address that references a landmark "X" in an area "A" gets added by the analysis module 207 to the bin of landmark "X" for area "A". The analysis module 207 can then determine at the end of the process that the bins with the most addresses are the most referenced landmarks (i.e., key landmarks) in a given area and are therefore prime candidates for geo- coding. Optionally, in certain embodiments, the analysis module 207, in connection with the communication module 203, can determine the frequency information, the popularity information, or a combination thereof relative to one or more reference landmarks by generating a graph of the relationship between the one or more landmarks. In addition, to determining the frequency information, the popularity information, or a combination thereof, the analysis module 207 can also determine how many other POIs, landmarks, or a combination that can also be geo-coded based on the geo-coding of the one or more highly referenced landmarks. More specifically, the analysis module 207, in connection with the communication module 203, can generate a graph that depicts (a) the one or more reference landmarks as one or more nodes of the at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes. The analysis module 207 can then determine the frequency information, the popularity information, or a combination thereof as well as the geo-coding potential based on the number of the one or more edges associated with the one or more nodes.

[0071] The storage module 207 is used in connection with the communication module 203 to manage the one or more address records determined from one or more stores and the one or more databases related to cities, areas, one or more landmarks, one or more prepositions, and one or more reference keywords in a given area contained in the location databases 109. In one embodiment, the storage module 207, in connection with the communication module 203, may be used to update the one or more databases of important landmarks in a given country in order to improve the future efficiency of the landmark- based geo-coding schemes. [0072] FIG. 3 is a flowchart of a process for geo-coding unstructured address information, according to one embodiment. FIG. 3 depicts a process 300 of parsing one or more unstructured address records. In one embodiment, the geo-coding platform 103 performs the process 300 and is implemented in, for instance, a chip set including a processor and a memory as shown in FIG. 7. In step 301, the geo-coding platform 103 determines one or more reference address records from the one or more stores. By way of example the one or more reference address records are one or more address records from one or more growth economies (e.g., India, parts of Asia-Pacific, and Africa). More specifically, these address records often do not adhere to any particular structure or scheme thereby making it difficult to employ traditional geo-coding schemes to such address records. In addition to lacking structure, the one or more address records may contain imprecise landmark references, colloquial references and/or abbreviations that may be different from their official names. Moreover, these address records may contain references to an area name, which may not have any official geo-boundaries. Further, address schemes and notions in growth economies often differ from one city to another based on the native language that is prevalent in that given city. For example, the word "chowk" in native language means a town square. This word, however, is native to Delhi and is uncommon in other regions of India. By way of another example, the one or more stores include, at least in part, one or more public address stores (e.g., generated and/or provided by YAHOO, NAVTEQ, etc.), one or more query input stores (e.g., a local search by a user for "Coconut Grove Restaurant, Marathahalli) and/or one or more crowdsourced stores (e.g., two or three landmarks inputted by a user upon request from his or her area of residence or work), or a combination thereof.

[0073] In step 303, the geo-coding platform 103 processes and/or facilitates a processing of one or more address records to determine one or more fields. By way of example, the one or more fields may include landmarks (e.g., a name of a business or POI, a building name, a shop name, etc.), street names, an area name, and a city name. However, determining the one or more fields is not a trivial task because, as previously discussed, the one or more address records are unstructured and often do not adhere to any particular scheme.

[0074] In step 305, the geo-coding platform 103 determines at least one sequence for parsing the one or more fields based, at least in part, on a geographical area associated with the one or more address records. By way of example, by examining large numbers of reference address records (e.g., over 1000 addresses) one or more sequences can become apparent that can assist the geo-coding platform 103 to determine at least one sequence for parsing the one or more fields. For example, in India most address records are delimited (e.g., with commas, semicolons, new line characters, etc.) and the first field often identifies a POI name (e.g., a building) and the last field often identifies a city name.

[0075] In step 307, the geo-coding platform 103 determines that the one or more address fields relate to one or more streets, an area, a city, a region, or a combination thereof, wherein the geo-coding of the one or more address records is further based, at least in part, on the one or more streets, the area, the city, the region, or a combination thereof. By way of example, geo-coding is the process of determining geographic coordinates (e.g., latitude-longitude coordinates) from other associated geographic data. Moreover, in many cases the geo-coordinates determined for one or more address records, one or more landmarks, or a combination thereof are then used to locate the one or more address records, the one or more landmarks, or a combination thereof on a map relative to the one or more streets, the area, the city, the region, or a combination therefore also referenced in the one or more address records.

[0076] In step 309, the geo-coding platform 103 causes, at least in part, a parsing of the one or more address records according to the at least one sequence to determine the one or more fields. As previously discusses, the geo-coding platform parses the one or more address records into different fields such as (a) landmark, (b) street name, (c) area name, and (d) city name. The parsing of the one or more address records into different fields is important because when the one or more input fields are compared and possibly matched by the geo-coding platform 103 against one or more related fields in one or more databases, the parsing into one or more different fields ensures that landmarks are matched against landmarks, street names against street names and so forth. [0077] In step 311, the geo-coding platform 103 determines one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks. By way of example, the geo-coding platform 103 assigns one or more scores to the first part of the delimited address record because research (e.g., observation of over 1000 address records) indicates that in this particular region (e.g., India) the first part of the address record is usually the business name or building name and as such often functions as a landmark in the given region. In addition, the geo-coding platform 103 can determine the one or more scores based on the one or more fields referencing one or more keywords such as (a) one or more prepositions that are indicative of one or more landmarks, (b) one or more reference keywords that are characteristic of one or more local or regional words for describing the one or more landmarks, or (c) a combination thereof.

[0078] In step 313, the geo-coding platform 103 causes, at least in part, a comparison of one or more values of the one or more fields to one or more keywords associated with the one or more landmarks, wherein the one or more scores, the one or more probabilities, or a combination thereof are based, at least in part, on the comparison. By way of example, the one or more keywords associated with one or more landmarks may include one or more propositions that are indicative of one or more landmarks such as "near," "next to," "opposite," etc., and common abbreviations (e.g., "NR for near" or "Opp for opposite). Similarly, the one or more keywords may include one or more reference keywords that are characteristic of one or more local or regional words for describing the one or more landmarks such as "building," "apartment," "station," "complex," "bank," "center," "colony," "showroom," "temple," "bar," "plaza," "hospital," "furniture," etc. as well as popular abbreviations such as "bldg.," "apt.," "clny.," etc. In addition, the one or more reference keywords may include certain words that make more sense in one city as opposed to another (e.g., "layout" is mostly found in Bangalore and some southern cities in India) and/or one or more words that are native to a particular city or area (e.g., "bagh" which means garden).

[0079] In step 315, the geo-coding platform 103 determines to specify one or more confidence levels for respective ones of the one or more keywords, wherein the one or more confidence levels are used to weight the comparison of the respective ones of the one or more keywords to determine one or more scores. By way of example, the geo-coding platform 103 may assign high confidence levels to prepositions that are indicative of one or more landmarks, reference keywords that are characteristic of one or more local or regional words for describing the one or more landmarks, or a combination thereof. In addition, the geo-coding platform 103 may assign a higher confidence level to a keyword such as "temple" compared to a keyword such as "furniture," which may or may not reference a building that is well-known in a given area (i.e., a landmark). Further, geo-coding platform 103 may assign a higher confidence level to a native keyword such as "bagh" (which means garden) compared to a native keyword such as "nagar" (which means a small area). [0080] FIG. 4 is a flowchart of a process for geo-coding unstructured address information in emerging economies, according to one embodiment. FIG. 4 depicts a process 400 of determining the key or important landmarks in a given area (e.g., India). In one embodiment, the geo-coding platform 103 performs the process 400 and is implemented in, for instance, a chip set including a processor and a memory as shown in FIG. 7. In step 401, the geo-coding platform 103 processes and/or facilitates a processing of one or more stores of one or more reference addresses to determine at least one set of one or more reference landmarks, wherein the at least one set of the one or more reference landmarks include, at least in part, the one or more landmarks. By way of example, in growth economies there are several landmarks that can be anything such as "mom and pop" stores, apartment buildings, malls, multiplexes, etc. As such, it is not feasible to determine the geo-coordinates for all of these landmarks. Therefore, it is important to identify the key landmarks for a given area. Moreover, once the geo-coding platform 103 determines the most referenced landmarks in a particular area and then geo-codes these landmarks whether by matching the one or more reference landmarks against one or more databases or manually geo-coding the one or more reference landmarks, the geo-coding platform 103 can then be used to assist with geo-coding numerous other address records that also reference these key or important landmarks. In addition, the one or more databases of important landmarks can be updated dynamically as a result, which can improve the future efficiency of one or more landmark-based geo-coding schemes. By way of example, more weight can be assigned to matches that match against the one or more important landmarks. Further, the one or more key landmarks can also be displayed on one or more maps for users to browse and/or can be provided as initial recommendations by various location-based services.

[0081] In step 403, the geo-coding platform 103 processes and/or facilitates a processing of the one or more reference records to determine frequency information, popularity information, or a combination thereof of related to the one or more reference landmarks, wherein the at least one set of the one or more reference landmarks are based, at least in part, on the frequency information, the popularity information, or a combination thereof. As previously discussed, in order to maximize available resources and the potential to geo-code numerous other address records it is important for the geo-coding platform 103 to first determine which landmarks in a given area are considered important among the people of that area.

[0082] In step 405, the geo-coding platform 103 determines one or more landmark references between at least one of the one or more reference address records and at least another one of the one or more reference address records. By way of example, one way to determine the popularity of one or more landmarks is to determine the frequency by which the one or more landmarks is referenced in one or more address records. The geo-coding platform 103 can determine this frequency information, this popularity information, or a combination thereof in a number of ways. For example, in one embodiment, the geo-coding platform 103 can generate one or more bins (e.g., a column in a dataset) for the one or more landmarks referenced in the one or more reference address records related to a particular area. In one example use case, the geo-coding platform 103 first determines the one or more landmarks referenced in the address record "ADDR1," "The Urban Nawaab, 4^th Floor, Below Roomali with a View, Opp Innovative Multiplex, Outer Ring Road, Marathahalli, Bangalore." Based on the parsing system method discussed above, the geo- coding platform 103 generates bins for the landmarks "Urban Nawaab," "Roomali with a View," and "Innovative Multiplex" for the area "Marathahalli" and the address record "ADDRl" is added to each of the bins. The geo-coding platform 103 next determines the one or more landmarks referenced in the address record "ADDR2," "Aspirations, 90/2, 2^nd Floor, Opposite Innovative Multiplex, Above Next Electronics, Marathahalli, Bangalore." Again, based on the parsing method previously discussed, geo-coding platform 103 generates bins for the landmarks "Aspirations" and "Next Electronics" for the area "Marathahalli" and the address record "ADDR2" is added to each of the bins as well as the bin related to "Innovative Multiplex." As a result, the bin related to "Innovative Multiplex" contains both address records "ADDR1" and "ADDR2." The geo-coding platform 103 is then able to determine based on the number of address records in each bin which one of the one or more landmarks are the most referenced landmarks and these landmarks are then designated by geo-coding platform 103 as the key landmarks for the area.

[0083] In step 407, the geo-coding platform 103 can optionally determine to create at least one graph depicting (a) the one or more reference landmarks as one or more nodes of the at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes. By way of example, based on the two example address records described above, "ADDRl" and "ADDR2," the geo-coding platform 103 can determine that the landmark "Innovative Multiplex" is a reference landmark constituting a node with two edges to the landmark references "Urban Nawaab," and "Aspiration." An illustrative example of this graph is depicted in FIG. 5. [0084] In step 409, the geo-coding platform 103 determines the frequency information, the popularity information, or a combination thereof based, at least in part, on the number of the one or more edges associated with the one or more nodes. By way of example, the geo-coding platform 103 can determine that "Innovative Multiplex" is a key landmark in the area (based on the small sampling) because it has edges with two other nodes. Moreover, based on this determination, it is apparent that by determining the geo-coordinates for "Innovative Multiplex," the geo-coding platform 103 can also approximate the geo-codes for the four other landmarks referenced in address records "ADDRl" and "ADDR2."

[0085] In step 411, the geo-coding platform 103 determines to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields. As previously discussed, once one or more important landmarks are geo-coded by the geo-coding platform 103, whether through comparison with one or more databases or through one or more manual geo-coding processes, the one or more address records can also be geo-coded. Moreover, the geo- coding platform 103 may also be used to geo-code a plethora of other address records based on the newly geo-coded address records. [0086] FIG. 5 is an illustrative example of a graph depicting (a) one or more reference landmarks (e.g., landmark 505) as one or more nodes and (b) one or more landmark references (e.g., landmarks 501, 503, 507, and 509) as one or more edges between the one or more nodes. More specifically, the system 100 determines the one or more reference landmarks as opposed to the one more landmark references by first parsing the example use case address records "ADDR1," "The Urban Nawaab, 4^th Floor, Below Roomali with a View, Opp Innovative Multiplex, Outer Ring Road, Marathahalli, Bangalore" and "ADDR2," "Aspirations, 90/2, 2^nd Floor, Opposite Innovative Multiplex, Above Next Electronics, Marathahalli, Bangalore." Based on the parsing method discussed above, the system 100 determines that "Urban Nawaab," "Roomali with a View," "Innovative Multiplex," "Aspirations," and "Next Electronics" represent landmarks 501, 503, 505, 507, and 509, respectively, for the area "Marathahalli." Moreover, the system 100 is able to determine based on the fact that landmark 505 shares two edges with landmarks 501 and 507, whereas the remaining landmarks only share one edge, that landmark 505 is the key landmark referenced in this sampling of address records and therefore is a prime candidate for geo-coding.

[0087] The processes described herein for geo-coding unstructured address information may be advantageously implemented via software, hardware, firmware or a combination of software and/or firmware and/or hardware. For example, the processes described herein, may be advantageously implemented via processor(s), Digital Signal Processing (DSP) chip, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGAs), etc. Such exemplary hardware for performing the described functions is detailed below.

[0088] FIG. 6 illustrates a computer system 600 upon which an embodiment of the invention may be implemented. Although computer system 600 is depicted with respect to a particular device or equipment, it is contemplated that other devices or equipment (e.g., network elements, servers, etc.) within FIG. 6 can deploy the illustrated hardware and components of system 600. Computer system 600 is programmed (e.g., via computer program code or instructions) to geo-code unstructured address information in emerging economies as described herein and includes a communication mechanism such as a bus 610 for passing information between other internal and external components of the computer system 600. Information (also called data) is represented as a physical expression of a measurable phenomenon, typically electric voltages, but including, in other embodiments, such phenomena as magnetic, electromagnetic, pressure, chemical, biological, molecular, atomic, sub-atomic and quantum interactions. For example, north and south magnetic fields, or a zero and non-zero electric voltage, represent two states (0, 1) of a binary digit (bit). Other phenomena can represent digits of a higher base. A superposition of multiple simultaneous quantum states before measurement represents a quantum bit (qubit). A sequence of one or more digits constitutes digital data that is used to represent a number or code for a character. In some embodiments, information called analog data is represented by a near continuum of measurable values within a particular range. Computer system 600, or a portion thereof, constitutes a means for performing one or more steps of geo-coding unstructured address information.

[0089] A bus 610 includes one or more parallel conductors of information so that information is transferred quickly among devices coupled to the bus 610. One or more processors 602 for processing information are coupled with the bus 610.

[0090] A processor (or multiple processors) 602 performs a set of operations on information as specified by computer program code related to geo-coding unstructured address information. The computer program code is a set of instructions or statements providing instructions for the operation of the processor and/or the computer system to perform specified functions. The code, for example, may be written in a computer programming language that is compiled into a native instruction set of the processor. The code may also be written directly using the native instruction set (e.g., machine language). The set of operations include bringing information in from the bus 610 and placing information on the bus 610. The set of operations also typically include comparing two or more units of information, shifting positions of units of information, and combining two or more units of information, such as by addition or multiplication or logical operations like OR, exclusive OR (XOR), and AND. Each operation of the set of operations that can be performed by the processor is represented to the processor by information called instructions, such as an operation code of one or more digits. A sequence of operations to be executed by the processor 602, such as a sequence of operation codes, constitute processor instructions, also called computer system instructions or, simply, computer instructions. Processors may be implemented as mechanical, electrical, magnetic, optical, chemical or quantum components, among others, alone or in combination.

[0091] Computer system 600 also includes a memory 604 coupled to bus 610. The memory 604, such as a random access memory (RAM) or any other dynamic storage device, stores information including processor instructions for geo-coding unstructured address information. Dynamic memory allows information stored therein to be changed by the computer system 600. RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at neighboring addresses. The memory 604 is also used by the processor 602 to store temporary values during execution of processor instructions. The computer system 600 also includes a read only memory (ROM) 606 or any other static storage device coupled to the bus 610 for storing static information, including instructions, that is not changed by the computer system 600. Some memory is composed of volatile storage that loses the information stored thereon when power is lost. Also coupled to bus 610 is a non- volatile (persistent) storage device 608, such as a magnetic disk, optical disk or flash card, for storing information, including instructions, that persists even when the computer system 600 is turned off or otherwise loses power.

[0092] Information, including instructions for geo-coding unstructured address information, is provided to the bus 610 for use by the processor from an external input device 612, such as a keyboard containing alphanumeric keys operated by a human user, a microphone, an Infrared (IR) remote control, a joystick, a game pad, a stylus pen, a touch screen, or a sensor. A sensor detects conditions in its vicinity and transforms those detections into physical expression compatible with the measurable phenomenon used to represent information in computer system 600. Other external devices coupled to bus 610, used primarily for interacting with humans, include a display device 614, such as a cathode ray tube (CRT), a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a plasma screen, or a printer for presenting text or images, and a pointing device 616, such as a mouse, a trackball, cursor direction keys, or a motion sensor, for controlling a position of a small cursor image presented on the display 614 and issuing commands associated with graphical elements presented on the display 614. In some embodiments, for example, in embodiments in which the computer system 600 performs all functions automatically without human input, one or more of external input device 612, display device 614 and pointing device 616 is omitted.

[0093] In the illustrated embodiment, special purpose hardware, such as an application specific integrated circuit (ASIC) 620, is coupled to bus 610. The special purpose hardware is configured to perform operations not performed by processor 602 quickly enough for special purposes. Examples of ASICs include graphics accelerator cards for generating images for display 614, cryptographic boards for encrypting and decrypting messages sent over a network, speech recognition, and interfaces to special external devices, such as robotic arms and medical scanning equipment that repeatedly perform some complex sequence of operations that are more efficiently implemented in hardware.

[0094] Computer system 600 also includes one or more instances of a communications interface 670 coupled to bus 610. Communication interface 670 provides a one-way or two-way communication coupling to a variety of external devices that operate with their own processors, such as printers, scanners and external disks. In general the coupling is with a network link 678 that is connected to a local network 680 to which a variety of external devices with their own processors are connected. For example, communication interface 670 may be a parallel port or a serial port or a universal serial bus (USB) port on a personal computer. In some embodiments, communications interface 670 is an integrated services digital network (ISDN) card or a digital subscriber line (DSL) card or a telephone modem that provides an information communication connection to a corresponding type of telephone line. In some embodiments, a communication interface 670 is a cable modem that converts signals on bus 610 into signals for a communication connection over a coaxial cable or into optical signals for a communication connection over a fiber optic cable. As another example, communications interface 670 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN, such as Ethernet. Wireless links may also be implemented. For wireless links, the communications interface 670 sends or receives or both sends and receives electrical, acoustic or electromagnetic signals, including infrared and optical signals, that carry information streams, such as digital data. For example, in wireless handheld devices, such as mobile telephones like cell phones, the communications interface 670 includes a radio band electromagnetic transmitter and receiver called a radio transceiver. In certain embodiments, the communications interface 670 enables connection to the communication network 105 for geo-coding unstructured address information to the UE 101.

[0095] The term "computer-readable medium" as used herein refers to any medium that participates in providing information to processor 602, including instructions for execution. Such a medium may take many forms, including, but not limited to computer-readable storage medium (e.g., non-volatile media, volatile media), and transmission media. Non- transitory media, such as non-volatile media, include, for example, optical or magnetic disks, such as storage device 608. Volatile media include, for example, dynamic memory 604. Transmission media include, for example, twisted pair cables, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, an EEPROM, a flash memory, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read. The term computer-readable storage medium is used herein to refer to any computer-readable medium except transmission media.

[0096] Logic encoded in one or more tangible media includes one or both of processor instructions on a computer-readable storage media and special purpose hardware, such as ASIC 620. [0097] Network link 678 typically provides information communication using transmission media through one or more networks to other devices that use or process the information. For example, network link 678 may provide a connection through local network 680 to a host computer 682 or to equipment 684 operated by an Internet Service Provider (ISP). ISP equipment 684 in turn provides data communication services through the public, world-wide packet-switching communication network of networks now commonly referred to as the Internet 690. [0098] A computer called a server host 692 connected to the Internet hosts a process that provides a service in response to information received over the Internet. For example, server host 692 hosts a process that provides information representing video data for presentation at display 614. It is contemplated that the components of system 600 can be deployed in various configurations within other computer systems, e.g., host 682 and server 692.

[0099] At least some embodiments of the invention are related to the use of computer system 600 for implementing some or all of the techniques described herein. According to one embodiment of the invention, those techniques are performed by computer system 600 in response to processor 602 executing one or more sequences of one or more processor instructions contained in memory 604. Such instructions, also called computer instructions, software and program code, may be read into memory 604 from another computer-readable medium such as storage device 608 or network link 678. Execution of the sequences of instructions contained in memory 604 causes processor 602 to perform one or more of the method steps described herein. In alternative embodiments, hardware, such as ASIC 620, may be used in place of or in combination with software to implement the invention. Thus, embodiments of the invention are not limited to any specific combination of hardware and software, unless otherwise explicitly stated herein.

[0100] The signals transmitted over network link 678 and other networks through communications interface 670, carry information to and from computer system 600. Computer system 600 can send and receive information, including program code, through the networks 680, 690 among others, through network link 678 and communications interface 670. In an example using the Internet 690, a server host 692 transmits program code for a particular application, requested by a message sent from computer 600, through Internet 690, ISP equipment 684, local network 680 and communications interface 670. The received code may be executed by processor 602 as it is received, or may be stored in memory 604 or in storage device 608 or any other non-volatile storage for later execution, or both. In this manner, computer system 600 may obtain application program code in the form of signals on a carrier wave. [0101] Various forms of computer readable media may be involved in carrying one or more sequence of instructions or data or both to processor 602 for execution. For example, instructions and data may initially be carried on a magnetic disk of a remote computer such as host 682. The remote computer loads the instructions and data into its dynamic memory and sends the instructions and data over a telephone line using a modem. A modem local to the computer system 600 receives the instructions and data on a telephone line and uses an infra-red transmitter to convert the instructions and data to a signal on an infra-red carrier wave serving as the network link 678. An infrared detector serving as communications interface 670 receives the instructions and data carried in the infrared signal and places information representing the instructions and data onto bus 610. Bus 610 carries the information to memory 604 from which processor 602 retrieves and executes the instructions using some of the data sent with the instructions. The instructions and data received in memory 604 may optionally be stored on storage device 608, either before or after execution by the processor 602.

[0102] FIG. 7 illustrates a chip set or chip 700 upon which an embodiment of the invention may be implemented. Chip set 700 is programmed to geo-code unstructured address information as described herein and includes, for instance, the processor and memory components described with respect to FIG. 6 incorporated in one or more physical packages (e.g., chips). By way of example, a physical package includes an arrangement of one or more materials, components, and/or wires on a structural assembly (e.g., a baseboard) to provide one or more characteristics such as physical strength, conservation of size, and/or limitation of electrical interaction. It is contemplated that in certain embodiments the chip set 700 can be implemented in a single chip. It is further contemplated that in certain embodiments the chip set or chip 700 can be implemented as a single "system on a chip." It is further contemplated that in certain embodiments a separate ASIC would not be used, for example, and that all relevant functions as disclosed herein would be performed by a processor or processors. Chip set or chip 700, or a portion thereof, constitutes a means for performing one or more steps of providing user interface navigation information associated with the availability of functions. Chip set or chip 700, or a portion thereof, constitutes a means for performing one or more steps of geo-coding unstructured address information. [0103] In one embodiment, the chip set or chip 700 includes a communication mechanism such as a bus 701 for passing information among the components of the chip set 700. A processor 703 has connectivity to the bus 701 to execute instructions and process information stored in, for example, a memory 705. The processor 703 may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi- core processor include two, four, eight, or greater numbers of processing cores. Altematively or in addition, the processor 703 may include one or more microprocessors configured in tandem via the bus 701 to enable independent execution of instructions, pipelining, and multithreading. The processor 703 may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP) 707, or one or more application-specific integrated circuits (ASIC) 709. A DSP 707 typically is configured to process real-world signals (e.g., sound) in real time independently of the processor 703. Similarly, an ASIC 709 can be configured to performed specialized functions not easily performed by a more general purpose processor. Other specialized components to aid in performing the inventive functions described herein may include one or more field programmable gate arrays (FPGA), one or more controllers, or one or more other special-purpose computer chips.

[0104] In one embodiment, the chip set or chip 700 includes merely one or more processors and some software and/or firmware supporting and/or relating to and/or for the one or more processors. [0105] The processor 703 and accompanying components have connectivity to the memory 705 via the bus 701. The memory 705 includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the inventive steps described herein to geo-code unstructured address information. The memory 705 also stores the data associated with or generated by the execution of the inventive steps.

[0106] FIG. 8 is a diagram of exemplary components of a mobile terminal (e.g., handset) for communications, which is capable of operating in the system of FIG. 1, according to one embodiment. In some embodiments, mobile terminal 801, or a portion thereof, constitutes a means for performing one or more steps of geo-coding unstructured address information. Generally, a radio receiver is often defined in terms of front-end and back-end characteristics. The front-end of the receiver encompasses all of the Radio Frequency (RF) circuitry whereas the back-end encompasses all of the base-band processing circuitry. As used in this application, the term "circuitry" refers to both: (1) hardware-only implementations (such as implementations in only analog and/or digital circuitry), and (2) to combinations of circuitry and software (and/or firmware) (such as, if applicable to the particular context, to a combination of processor(s), including digital signal processor(s), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions). This definition of "circuitry" applies to all uses of this term in this application, including in any claims. As a further example, as used in this application and if applicable to the particular context, the term "circuitry" would also cover an implementation of merely a processor (or multiple processors) and its (or their) accompanying software/or firmware. The term "circuitry" would also cover if applicable to the particular context, for example, a baseband integrated circuit or applications processor integrated circuit in a mobile phone or a similar integrated circuit in a cellular network device or other network devices. [0107] Pertinent internal components of the telephone include a Main Control Unit (MCU) 803, a Digital Signal Processor (DSP) 805, and a receiver/transmitter unit including a microphone gain control unit and a speaker gain control unit. A main display unit 807 provides a display to the user in support of various applications and mobile terminal functions that perform or support the steps of geo-coding unstructured address information. The display 807 includes display circuitry configured to display at least a portion of a user interface of the mobile terminal (e.g., mobile telephone). Additionally, the display 807 and display circuitry are configured to facilitate user control of at least some functions of the mobile terminal. An audio function circuitry 809 includes a microphone 811 and microphone amplifier that amplifies the speech signal output from the microphone 811. The amplified speech signal output from the microphone 811 is fed to a coder/decoder (CODEC) 813.

[0108] A radio section 815 amplifies power and converts frequency in order to communicate with a base station, which is included in a mobile communication system, via antenna 817. The power amplifier (PA) 819 and the transmitter/modulation circuitry are operationally responsive to the MCU 803, with an output from the PA 819 coupled to the dup lexer 821 or circulator or antenna switch, as known in the art. The PA 819 also couples to a battery interface and power control unit 820.

[0109] In use, a user of mobile terminal 801 speaks into the microphone 811 and his or her voice along with any detected background noise is converted into an analog voltage. The analog voltage is then converted into a digital signal through the Analog to Digital Converter (ADC) 823. The control unit 803 routes the digital signal into the DSP 805 for processing therein, such as speech encoding, channel encoding, encrypting, and interleaving. In one embodiment, the processed voice signals are encoded, by units not separately shown, using a cellular transmission protocol such as enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), satellite, and the like, or any combination thereof.

[0110] The encoded signals are then routed to an equalizer 825 for compensation of any frequency-dependent impairments that occur during transmission though the air such as phase and amplitude distortion. After equalizing the bit stream, the modulator 827 combines the signal with a RF signal generated in the RF interface 829. The modulator 827 generates a sine wave by way of frequency or phase modulation. In order to prepare the signal for transmission, an up-converter 831 combines the sine wave output from the modulator 827 with another sine wave generated by a synthesizer 833 to achieve the desired frequency of transmission. The signal is then sent through a PA 819 to increase the signal to an appropriate power level. In practical systems, the PA 819 acts as a variable gain amplifier whose gain is controlled by the DSP 805 from information received from a network base station. The signal is then filtered within the dup lexer 821 and optionally sent to an antenna coupler 835 to match impedances to provide maximum power transfer. Finally, the signal is transmitted via antenna 817 to a local base station. An automatic gain control (AGC) can be supplied to control the gain of the final stages of the receiver. The signals may be forwarded from there to a remote telephone which may be another cellular telephone, any other mobile phone or a land-line connected to a Public Switched Telephone Network (PSTN), or other telephony networks.

[0111] Voice signals transmitted to the mobile terminal 801 are received via antenna 817 and immediately amplified by a low noise amplifier (LNA) 837. A down-converter 839 lowers the carrier frequency while the demodulator 841 strips away the RF leaving only a digital bit stream. The signal then goes through the equalizer 825 and is processed by the DSP 805. A Digital to Analog Converter (DAC) 843 converts the signal and the resulting output is transmitted to the user through the speaker 845, all under control of a Main Control Unit (MCU) 803 which can be implemented as a Central Processing Unit (CPU). [0112] The MCU 803 receives various signals including input signals from the keyboard 847. The keyboard 847 and/or the MCU 803 in combination with other user input components (e.g., the microphone 811) comprise a user interface circuitry for managing user input. The MCU 803 runs a user interface software to facilitate user control of at least some functions of the mobile terminal 801 to geo-code unstructured address information. The MCU 803 also delivers a display command and a switch command to the display 807 and to the speech output switching controller, respectively. Further, the MCU 803 exchanges information with the DSP 805 and can access an optionally incorporated SIM card 849 and a memory 851. In addition, the MCU 803 executes various control functions required of the terminal. The DSP 805 may, depending upon the implementation, perform any of a variety of conventional digital processing functions on the voice signals. Additionally, DSP 805 determines the background noise level of the local environment from the signals detected by microphone 811 and sets the gain of microphone 811 to a level selected to compensate for the natural tendency of the user of the mobile terminal 801.

[0113] The CODEC 813 includes the ADC 823 and DAC 843. The memory 851 stores various data including call incoming tone data and is capable of storing other data including music data received via, e.g., the global Internet. The software module could reside in RAM memory, flash memory, registers, or any other form of writable storage medium known in the art. The memory device 851 may be, but not limited to, a single memory, CD, DVD, ROM, RAM, EEPROM, optical storage, magnetic disk storage, flash memory storage, or any other non- volatile storage medium capable of storing digital data. [0114] An optionally incorporated SIM card 849 carries, for instance, important information, such as the cellular phone number, the carrier supplying service, subscription details, and security information. The SIM card 849 serves primarily to identify the mobile terminal 801 on a radio network. The card 849 also contains a memory for storing a personal telephone number registry, text messages, and user specific mobile terminal settings.

[0115] While the invention has been described in connection with a number of embodiments and implementations, the invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims. Although features of the invention are expressed in certain combinations among the claims, it is contemplated that these features can be arranged in any combination and order.

Claims

1. A method comprising:

processing and/or facilitating a processing of one or more address records to determine one or more fields;

determining one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks; and

determining to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields.

2. A method of claim 1, further comprising:

causing, at least in part, a comparison of one or more values of the one or more fields to one or more keywords associated with the one or more landmarks, wherein the one or more scores, the one or more probabilities, or a combination thereof are based, at least in part, on the comparison.

3. A method of claim 2, wherein the one or more keywords include, at least in part, (a) one or more prepositions that are indicative of the one or more landmarks, (b) one or more reference keywords that are characteristic of one or more local or regional words for describing the one or more landmarks, or (c) a combination thereof.

4. A method according to any of claims 2 and 3, further comprising:

determining to specify one or more confidence levels for respective ones of the one or more keywords,

wherein the one or more confidence levels are used to weight the comparison of the respective ones of the one or more keywords to determine the one or more scores.

5. A method according to any of claims 1-4, further comprising:

determining that the one or more fields relate to one or more streets, an area, a city, a region, or a combination thereof,

wherein the geo-coding of the one or more address records is further based, at least in part, on the one or more streets, the area, the city, the region, or a combination thereof.

6. A method according to any of claims 1-5, further comprising:

processing and/or facilitating a processing of one or more stores of one or more reference addresses to determine at least one set of one or more reference landmarks,

wherein the at least one set of the one or more reference landmarks include, at least in part, the one or more landmarks.

7. A method of claim 6, further comprising:

determining one or more reference address records from the one or more stores;

processing and/or facilitating a processing of the one or more reference records to determine frequency information, popularity information, or a

combination thereof of related to the one or more reference landmarks,

wherein the at least one set of the one or more reference landmarks are based, at least in part, on the frequency information, the popularity information, or a combination thereof.

8. A method of claim 7, wherein the one or more stores include, at least in part, one or more public address stores, one or more query input stores, one or more crowdsourced address stores, or a combination thereof.

9. A method according to any of claims 7 and 8, further comprising: determining one or more landmark references between at least one of the one or more reference address records and at least another one of the one or more reference address records;

determining to create at least one graph depicting (a) the one or more reference landmarks as one or more nodes of the at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes; and

determining the frequency information, the popularity information, or a combination thereof based, at least in part, on the number of the one or more edges associated with the one or more nodes.

10. A method according to any of claims 1-9, further comprising:

determining at least one sequence for parsing the one or more fields based, at least in part, on a geographical area associated with the one or more address records;

causing, at least in part, a parsing of the one or more address records according to the at least one sequence to determine the one or more fields.

11. An apparatus comprising:

at least one processor; and

at least one memory including computer program code for one or more programs,

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

process and/or facilitate a processing of one or more address records to determine one or more fields;

determine one or more scores for the one or more fields based, at least in part, on one or more probabilities that the one or more fields specify one or more landmarks; and

determine to geo-code the one or more address records based, at least in part, on a geo-coding of the one or more landmarks identified in the at least one of the one or more fields.

12. An apparatus of claim 11, wherein the apparatus is further caused to:

cause, at least in part, a comparison of one or more values of the one or more fields to one or more keywords associated with the one or more landmarks, wherein the one or more scores, the one or more probabilities, or a combination thereof are based, at least in part, on the comparison.

13. An apparatus of claim 12, wherein the one or more keywords include, at least in part, (a) one or more prepositions that are indicative of the one or more landmarks, (b) one or more reference keywords that are characteristic of one or more local or regional words for describing the one or more landmarks, or (c) or a combination thereof.

14. An apparatus according to any of claims 12 and 13, wherein the apparatus is further caused to:

determine to specify one or more confidence levels for respective ones of the one or more keywords,

wherein the one or more confidence levels are used to weight the

comparison of the respective ones of the one or more keywords to determine the one or more scores.

15. An apparatus according to any of claims 11-14, wherein the apparatus is further caused to:

determine that the one or more fields relate to one or more streets, an area, a city, a region, or a combination thereof,

wherein the geo-coding of the one or more address records is further based, at least in part, on the one or more landmarks, the one or more streets, the area, the city, the region, or a combination thereof.

16. An apparatus according to any of claims 11-15, wherein the apparatus is further caused to: process and/or facilitate a processing of one or more stores of one or more reference addresses to determine at least one set of one or more reference landmarks,

17. An apparatus of claims 16, wherein the apparatus is further caused to:

determine one or more reference address records from the one or more stores;

process and/or facilitate a processing of the one or more reference records to determine frequency information, popularity information, or a combination thereof of related to the one or more reference landmarks,

18. An apparatus of claim 17, wherein the one or more stores include, at least in part, one or more public address stores, one or more query input stores, one or more

crowdsourced address stores, or a combination thereof.

19. An apparatus according to any of claims 17 and 18, wherein the apparatus is further caused to:

determine one or more landmark references between at least one of the one or more reference address records and at least another one of the one or more reference address records;

determine to create at least one graph depicting (a) the one or more reference landmarks as one or more nodes of the at least one graph and (b) the one or more landmark references as one or more edges between the one or more nodes; and

determine the frequency information, the popularity information, or a combination thereof based, at least in part, on the number of the one or more edges associated with the one or more nodes.

20. An apparatus according to any of claims 11-19, wherein the apparatus is further caused to:

determine at least one sequence for parsing the one or more fields based, at least in part, on a geographical area associated with the one or more address records;

cause, at least in part, a parsing of the one or more address records according to the at least one sequence to determine the one or more fields.

21. An apparatus according to any of claims 11-20, wherein the apparatus is a mobile phone further comprising:

user interface circuitry and user interface software configured to facilitate user control of at least some functions of the mobile phone through use of a display and configured to respond to user input; and

a display and display circuitry configured to display at least a portion of a user interface of the mobile phone, the display and display circuitry configured to facilitate user control of at least some functions of the mobile phone.

22. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least a method of any of claims 1-10.

23. An apparatus comprising means for performing a method of any of claims 1-10.

24. An apparatus of claim 23, wherein the apparatus is a mobile phone further comprising:

25. A computer program product including one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the steps of a method of any of claims 1-10.

26. A method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform a method of any of claims 1-10.

27. A method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the method of any of claims 1-10.

28. A method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on the method of any of claims 1-10.