BRPI0615323A2 - local search, geocoding and indexing methods and local search systems - Google Patents

Abstract

Local Search, Geocoding and Indexing Methods and Local Search Systems Summary A system receives yellow page data, map provider data and document data in response to a local search question and geocodes the data to assign a geographic identifier and combine at least one address associated with the local search question, The system also indexes the geocoded data to determine business information and location information associated with the local search question, The system even provides local search results and a map based on the indexed data.

Description

"Local Search Methods, Geocoding and Indexing, and Local Search Systems"

Descriptive Report

Background

The embodiments described herein generally relate to information retrieval and more particularly to the identification of local search results.

The World Wide Web ("Web") contains a vast amount of information. Locating a desired piece of information, however, can be challenging. This problem can be complex because the amount of Web information and the number of new users without Web search experience is rapidly increasing.

Search engines try to return hyperlinks to webpages the user is interested in. Generally, search systems base their determination of user interest on search terms (called search queries) entered by the user. The goal of the search engine may be to provide links to relevant, high quality results (eg web pages) to the user based on the search issue. Typically, the search engine performs this by comparing terms in the search query with a body of pre-stored web pages. Web pages that contain user search terms may be called "hit" or "search results" and may be returned to the user as links.

Local search engines attempt to return relevant web pages and / or business listings within a specific geographic area. In some countries, detailed address information is not available for some businesses. As a result, it may be difficult to perform local searches.

Summary According to one aspect, a method may include receiving yellow page data, third map provider data, and document data in response to a local search question and geocoding at least one of the yellow page data, the data from the data provider. third-party maps and document data to assign a geographic identifier and match at least one address within the local search query. The method may also include indexing geocoded data to identify business information and location information that corresponds to the local search issue and provide local search results and a third-party map based on identified business information and location information.

In another aspect, a geocoding method based on a local search query may include receiving data from third-party map providers and yellow page data, generating an address based on the local search query, parsing the address, locating matching prefixes, and more. long at the address to identify at least part of the address, and find a match at the address to verify the address.

In yet another aspect, an indexing method based on a local search issue may include pre-processed yellow pages to a predetermined format, extracting business information from document data, storing business information in a repository, and index address information from data from third-party map providers. The method may also include grouping yellow page data and third-party map provider data and highlighting fragments in document data. For a point location, the method may include adjusting a search distance for the local search question to a predetermined distance. For a limited location, the method may further include adjusting the search distance to approximately a maximum distance of a centroid from the limited location to the limited location.

As an additional aspect, a method may include generating a list of synonyms related to a local quest question, rewriting the local search question to expand the issue, generating local search results based on the expanded question, obtaining a map from a third-party map provider based on local search results and generate ads based on geographic information related to local search results.

In another aspect, a system may include an indexer for receiving data from third-party map providers, yellow page data and document data, preprocessing yellow page data to determine business information, extracting business information from document data, identify location information in a local search issue, and index data address data from third-party map providers. The system may also include a geocoder to receive information from the indexer and assign geographic identifiers and a front end server to receive information from the geocoder, rewrite the local search query, get mapped data from third party map providers and generate the results from Local search based on local search issue.

In yet another aspect, a system may include means for receiving yellow page data, third-party map depleting data and document data in response to a local search query and means for geocoding at least one of the yellow page data, third-party map providers and document data to assign a geographic identifier and compare at least one address within the local search query. The system may also include means for indexing geocoded data to identify business information and location information corresponding to the local search issue and means for providing local search results and a third-party map based on business information and identifiable location information. -Each.

In an additional aspect, a system may include a memory for storing an instruction group and a processor for executing instructions in memory. The processor can identify a position associated with a local search question, identify local search results relevant to the local search query and associated with the identified position, identify an identifier for each of a local search result group, and retrieve from a third-party map provider is a map associated with the identified position, where the map identifies a position of at least one local search result in the local search result group.

According to ... an additional aspect, a method may include receiving a local search query, identifying a location associated with the local search query, identifying a set of search results relevant to the local search query and associated with the identified location and identify an identifier for each of a search result group. The method may also include providing the identifier for each of the groups; search results to a third-party map provider and receive from the third-party map provider a map associated with an identified affix, where the map identifies a position of at least one search result in the search result group.

In another aspect, a method may include generating a token list, identifying a potential address within a web document, and analyzing the potential address from an early stage to determine if the potential address includes a token associated with a city. The method may also include further analyzing the potential address to determine if the potential address includes a form associated with a district, identifying a longer comparison form at the potential address after the form associated with the city or the form associated with the district, and determining whether the potential address This is a real address based on the form associated with the city, the form associated with the district, and the longest identified form.

Brief Description of the Drawings

The accompanying drawings, which are incorporated and form part of this Report, illustrate one or more embodiments of the invention and, together with the description, explain aspects of the invention. In the drawings:

Figure 1 is a diagrammatic overview of an exemplary implementation described herein;

Figure 2 is a diagram of an exemplary network in which the described systems and methods may be implemented;

Figure 3 is an exemplary diagram of a client or server within the exemplary network of Figure 2;

Figure 4 is a functional block diagram of an exemplary system for identifying local search results and providing a map associated with identified locations;

Figure 5 is an exemplary diagram of an index / document repository of the exemplary system of Figure 4;

Figure 6 is an exemplary diagram of an encoder of the exemplary system of Figure 4;

Figure 7 is an exemplary diagram of an indexer of the exemplary system of Figure 4;

Figure 8 is an exemplary diagram of a front end server of the exemplary system of Figure 4; Figure 9 is a diagram of exemplary local search results and a map generated by the exemplary system of Figure 4;

Figures 10A-10D are flowcharts of an exemplary process for identifying local search results and providing a map associated with identified locations.

Detailed Description

The following detailed description of the invention relates to the accompanying drawings. The same reference numerals in different drawings may identify the same or similar elements. Also the following detailed description does not limit the invention.

In some countries, such as China, for example, map data and yellow page data may not be available from a single provider and must be obtained from several different providers: '- Due to export restrictions, it may not be possible. obtain detailed map data to provide the map of an area or achieve the actual latitude and longitude of addresses within the area. As a result, address approximation can be used for address geocoding. When results are sent from a local search to the user, the local results page may include a list of relevant results and a pointer to the map provider (third party) server. The map provider may be responsible for generating the map displayed to the user.

Evaluation

The implementations described herein may identify local search results and generate a map associated with identified locations. For example, in one embodiment, as shown in Figure 1, a system may receive a local search query entry by a user and may identify a position associated with the local search query. The system can identify a set of local search results (for example, "A" through até "search results) that may be related to the local search question and may be associated with the identified position. Local search results may include links to documents that may relate to the local search issue.The system may identify an identifier for a local search result group and may provide an identifier for a map provider.The system may receive a map associated with the identified location of the search provider. maps.The map could identify a position of at least one search result (for example, search result "A" as shown in Figure 1) in the local search result group.

A "document" as the term is used herein should be interpreted broadly to include any machine-readable and machine-storable product. A document may include, for example, an e-mail, a file, a file combination, one or more files with embedded links to other files, a newsgroup posting a blog, a Web ad, and so on. In the context of the Internet, a common document is a web page. Web pages often include textual information and may include embedded information (such as meta-information, images, hyperlinks, etc.) and / or embedded instructions (such as JavaScript, etc.).

AIinkt, as the term is used herein, should be interpreted broadly to include any reference to / from a document from / to another document or another part of the same document.

Exemplary Network Configuration

Figure 2 is an exemplary diagram of a network 200 in which the systems and methods described herein may be implemented. Network 200 may include multiple clients 210 connected to .., · multiple servers 220-240 via a network 250. Two clients-210 and three servers 220-240 have been illustrated as connected to network 250 for simplicity. In practice, there may be more or less server clients. Also, in some instances, a client may perform one or more functions of a server and / or a server may perform one or more functions of a client.

Clients 210 may include client entities. An entity can be defined as a device, such as a personal computer, cordless telephone, personal digital assistant (PDA), laptop, or other type of computing or communication device, thread or process that runs on one of these. devices and / or an object executable by one of these devices. 220-240 servers may include: server entities that gather, process, search, and / or maintain documents.

In one implementation, server 220 may include a local search system 225 usable by clients 210. Server 220 may span a body of documents, index documents, and store information associated with documents in a document repository. Any combination of servers 220-240 may implement local search system 225 to identify local search results and provide a map associated with identified locations.

Although 220-240 servers are shown as separate entities, it may be possible for one or more of the 220-240 servers to perform one or more of the functions of another or more 220-240 servers. For example, it may be possible for two or more servers220-240

implemented as a single server. It may also be possible for a single of the 220-240 servers to be deployed as two or more separate (and possibly distributed) devices.

Network 250 may include a local area network (LAN), a remote network (WAN), a network. , such as the Public Switched Telephone Network (PSTN) or a cellular network, an intranet, the Internet, or a combination of networks. 210 clients and 220-240 servers can connect to network 250 via wired, wireless, and / or optical connections.

Exemplary Architecture

Client / Server

Figure 3 is an exemplary diagram of a client or server entity (hereinafter referred to as "client / server entity"), which may correspond to one or more clients 210 and servers 220-240. The client / server entity may include a bus 310 , a processor 320, a main memory 330, a read-only memory (ROM) 340, a storage device 350, an input device 360, an output device 370, and a communication interface 380. Bus 310 may include a path which allows communication between client / server entity elements.

Processor 320 may include a processor, microprocessor, or processing logic that can interpret and execute instructions. Main memory 330 may include a random access memory (RAM) or other type of dynamic memory device that may store information and instructions for execution by processor 320. ROM 340 may include a ROM device or other type of static storage device that it may store static information and instructions for use by the processor 320. The storage device 350 may include a magnetic and / or optical recording medium and its corresponding chip.

The input device 360 may include a mechanism that allows the operator to input information to the client / server such as a keyboard, mouse, pen, sound recognition and / or biometric mechanisms etc. The output device 370 may include a mechanism for outputting information to the operator including a speaker etc. Communication interface 380 may include any transceiver-like mechanisms that enable the client / server entity to communicate with other devices and / or systems. For example, communication interface 380 may include mechanisms for communicating with another device or system via the network, such as network 250.

The client / server entity may perform certain operations as will be described in detail below. The client / server entity may perform these operations in response to the processor 320 executing software instructions contained on a computer readable medium such as memory 330. A computer readable medium may be defined as a physical or logical memory device and / or carrier.

Software instructions may be read to memory330 from another computer readable medium, such as data storage device 350, or from another device via communication interface 380. Software instructions contained in memory 330 may cause processor 320 performs processes which will be described later. Alternatively, physical circuits may be used in place or in combination with software instructions to implement processes described herein. Accordingly, the implementations described herein are not limited to any specific combination of hardware and software circuits.

Local Search System

Figure 4 is a functional block diagram of an exemplary system (e.g., local search system 225) for identifying local search results and providing an associated map with identified locations. According to one implementation, one or more of system functions 225, as described below, may be performed by a server (e.g. server 220), a portion of server 220, or a combination of servers (for example, servers 220). -240). According to another implementation, one or more of these functions may be performed by a separate entity from server 220, such as the client (e.g., client 210), a computer associated with server 220, or one of servers 230 or 240.

As shown in Figure 4, system 225 may include map providers 400, yellow page data 405, web document data 410, an index / document repository 415, address and point identification information (ID). of interest (POI) 420, address (FP) fingerprint and POI ID mapping information 425, a 430 geocoder, a 435 indexer, a 440 front end server, map Uniform Resource Locator (URL) information 445 and local450 search results. Map provider data 400, yellow page data 405, and web document data 410 can be provided to the indexer 435 and map provider data 400 can still be used to derive POI 420e address / lD information POI ID mapping information and FP 425 addresses. Indexer 435 can connect to an index / document repository 415 and geocoder 430 and POI ID / address information 420 can be provided to geocoder 430. front end server 440 can connect to geocoder 430 and index / document repository 415 and can receive POI ID and FP 425 address mapping information. Front end server 440 can generate map URL information 445 and search results System 225 may alternatively include other component connections and / or interrelationships not shown in Figure 4.

In general, geocoder 430 can receive POI ID / address information and / or information from indexer 435, can assign geographic identifiers (for example, locations, coordinates, etc.) to objects, and can provide output to the frontend server. 440. Indexer 435 may receive data from the map provider400, yellow page 405 data and / or Web 410 document data, can preprocess yellow page 405 data to determine business information, extract business information from document data. 410, identify location information in a search query, index address data from map providers 400, and can provide outputs to index / document repository 415 and / or geocoder 430. Front end server 440 can receive information address POI and FP ID numbers, information from geocoder 430, and / or index repository information / d 415, you can rewrite the search question and can generate map URL information 450, local search results 450, and / or geographic information for use by an ad server (not shown).

Map Provider Data

There can be two types of data for Chinese address information: map data and yellow page data. Data from map providers 400 may include a variety of information. For example, in one embodiment, a third-party map provider may provide a set of POIs (for example, businesses and other places of interest, such as museums, parks, hospitals, schools, etc.) and their addresses to cities in China. There may be POI ID information for each POI. Due to "legal restrictions, the map operator may not provide latitude and longitude information for each POI. They may, however, split a map into grids (for example, three hundred meters by three hundred meters) and may provide a grid index. for each POI and a program to compute the distance between grids. Map provider data 400 may be periodically updated (eg daily, weekly, monthly, etc.) and during each update the POI ID may change.

In another implementation, map provider data 400 may include the following information: (1) a normal POI which may contain a business name, address, telephone number, and grid index; (2) a road POI that may contain a street name and a grid index of the center of the street; and / or (3) a postcode POI which may contain postcodes and an approximate center grid index of the postcodes.

In yet another implementation, there may be themes with map provider data 400. For example, map provider data 400 may contain a portion of an address, but. may be missing another part of the address. The street number, for example, may be missing from map provider data 400 due to restrictions in China (for example, only 20-30% of POIs may have double numbers). As a result, data from map providers 400 may only include the street name of the POI or some higher level of abstraction. Also or alternatively, the phone number may be missing for some of the map provider data POIs 400. Also or alternatively, the addresses provided by the map depraving data 400 may be improperly formatted.

Yellow Page Data

Yellow page data 405 may include a variety of information and may be received from multiple sources (eg third party providers). For example, in one implementation, yellow page 405 data may include address information (for example, county, city, province) and / or telephone number for POIs, business names, e-mail addresses, facsimile numbers, websites, executive names, business descriptions, SIC style categories, business types, etc. In another embodiment, the data on the pages 405 may not contain any latitude and longitude information. As a result, complete (or substantially complete) information regarding POIs (for example, address information, telephone numbers, and map positions) can be deduced from map provider data 400 and yellow page data405.

Web Document Data

Web 410 document data may include a variety of information. For example, in one embodiment, Web 410 data may include an e-mail, a file, a combination of files, one or more files linked to another file, a newsgroup, a blog, a Web ad, a Web page. Web (which may include IO textual information and may include embedded information (such as metadata, images, hyperlinks, etc.) and / or embedded instructions (such as JavaScript, etc.), business information (eg, address, phone number, etc.) etc. Web document data 410 may also include documents located based on a local search issue.

POI ID / Address Information

POI ID 420 information may include a variety of information. For example, in one implementation, POI ID / address information may include addresses extracted from map provider data 400, POI IDs extracted from map provider data 400, and so forth. In another embodiment, address POI ID information 420 may include the following Chinese address information: address data provided by map provider data 400 (e.g., POI addresses, street centers); POIs (eg schools, parks, buildings, hospitals, etc.); postcode centers (ie within an area covered by a postcode); additional cities that may not be included in the list provided by map provider data 400, etc.

Address FP Mapping Information

and POI ID Address FP information and POI ID 425 may include a variety of information. For example, in one implementation, the address FP / POI ID 425 information may include a mapping between address fingerprints (FPs) and corresponding POI IDs, etc. Mapping between eID address FPs of matching POIs can be used by the frorvt end440 server to look up the POI ID for each local search result, as described in detail below. In an alternative embodiment, the POI ID can be derived directly without mapping between address POFs and corresponding POI IDs. In this alternative, information 425 may include the ID of directly derived POIs.

While exemplary information included in map provider data 400, yellow page data 405, web document data 410, POI ID / address information, and FP address mapping / POI ID 425 information have been described above, in other implementations, information Additional or different addresses that may be useful in identifying local search results may be included in the example information. The figures. 5-8 are exemplary diagrams of some components of system 225 of Figure 4.

Index / Document Repository

The index / document repository 415 may be provided in a single memory device (e.g. main memory330, ROM 340 and / or storage device 350). The index / document repository 415, as shown in Figure 5, can store a variety of document related information, yellow page 405 data, and / or map provider data 400. For example, in one implementation, the index / index repository documents 415 can store the following information regarding Chinese addresses: address data provided by map deprecating data 400 (e.g., POI addresses, double centers); POIs (eg schools, parks, buildings, hospitals, etc.), postcode centers (ie the center of an area covered by a postcode); additional cities that may not be included in the list provided by map provider data 400; etc.

In another embodiment, as shown in Figure 5, the index / document repository 415 may include a field [province] 500, a field [city] 510, a field [district] 520, and a field [street] 530 (which may be additionally or alternatively include an address field and / or a POI name field). The following examples may correspond to Chinese address information stored in index / document repository 415:

[Beijing City] [XiCheng District] [Bei-LiShi Road];

[Beijing City] [HaiDian District] [YiHeYuan Niimero Road 5];

[Beijing City] [HaiDian District] [Beijing University]; and [JiangSu Province] [Nan-Jing City] [GuLou District] [HanZhong Road].

In yet another embodiment, the index / document repository 415 may include an address fingerprint (FP) field 540 and a precision field of FP 550. Each address may be treated as a point by geocoder 430 with an accuracy ofFP address and PF (for example, buildings may have a higher PF accuracy than street centers). An address FP can be an address-based fingerprint (for example, an address-based hash value) that can be used to look up the POI ID to display the correct map. For example, a FP 570 generator can receive an address (for example, field [province] 500, field [city] 510, field [district] 520, field [street] 530 etc.) and can generate an FP of addresses (for example, field [FP ] 540) and an FP accuracy (for example, exact field [FP] 550) based on the address. Address FP and FP accuracy can be used by a POI580 ID lookup table to look up the POI ID to display the correct map (for example, with local search results). The FP 570 generator and POI ID lookup table 580 may be provided on geocoder 430, indexer 435, or front end server 440.

Still in an additional embodiment, document index repository 415 may include a [zcode] field 560 associated with the address. An associated zcode may include a code such as a postcode which, in the case of China, may be computed from the six-digit administrative code for districts in China. Locations, such as JiangSu Province, Beijing City, Beijing CityXiCheng District, can be computed by geocoder 430 as boundaries that contain all point locations within them.

Address variants can also be determined and stored in the index / document repository 415 to increase calls. For example, unique character synonyms can be identified for provinces and cities (eg Shanghai City —► Lu; HeBei Province -> Qi). Alternatively, or alternatively, parts of the addresses may be omitted (eg Shanghai City -> Shanghai; HaiDian District -> HaiDian; HuaiHai Central Road —► HuaiHai Road). Alternatively or alternatively, synonyms may be included for famous places (eg Shanghai City Temple —► Old City Temple; LiuRong Temple —► LiuRong Ta).

Although Figure 5 shows exemplary information included in the index / document repository 415, in other implementations, the index / document repository 415 may include any information that may be useful in identifying local search results.

GeocodingThe 430 geocoding, as shown in Figure 6, can perform a variety of tasks to help identify local search results. In one embodiment, for example, geocoding 430 may assign geographic identifiers (e.g., positions, coordinates, etc.) to objects. For example, geocoder 430 can compare addresses with addresses in the index / document repository 415. Output from geocoder 430 can be used for a variety of purposes. For example, yellow page data405 can be analyzed to determine business information (for example, address, phone number, e-mail address, facsimile number, hours of operation, etc.) for POIs, Business can be extracted from Web 410 document data and / or location information provided in a search query can be identified.

In order to index yellow page data 405, indexer 435 may need to determine position on the map by searching Chinese addresses. This can involve a variety of issues. For example, accurate location and detailed address information for most addresses in China is not readily available. Chinese addresses do not have a well-defined format and hierarchy. Possible components of a Chinese address may include city, district, city, village, road, street, street number, and building. Yellow page 405 data may be in formal form (ie not conforming to any particular form or format), especially in rural areas, and, for some POIs, there are no corresponding address components available. Exemplary Chinese addresses may include:

ShenZhen City HeGang CityAnLiang Village AnLiang Road Number 172 JingCheng Building;

ShenZhen Town LongHua Town MingZhiMingLe Office Complex ShenZhen Town FuHong RoadShiMao Block A 17 ° Floor; and

Beijing City HaiDian District SiJiQingXiao-Fu.

The 430 geocoder can better compare addresses on yellow page 405 data with addresses provided on map provider data 400 and get the most accurate map position possible. The geocoder 430 may include an address list generator 600, an analyzer 610, a longer coincidence prefix locator 620, a combination locator 630, a geocoding unit of question 640, and so forth. The 430 encoder components can perform various tasks for each address (for example, ShenZhen City HeGang City AnLi-ang Village AnLiang Road Number 172 JingCheng Building).

The address book generator 600 can receive map deprecating data 400 and yellow page data 405 and can generate a mailing list (also called tokens) with only provinces, cities, districts, street names, addresses, POI names or combinations. from the map provider data 400 and / or yellow page data 405. For each address, the analyzer 610 may attempt to analyze the city from the beginning of the address. For example, "ShenZhen City" can be parsed by address analyzer 610. Analyzer 610 may also attempt to analyze the district of the address. For example, since a district is absent from the exemplary address described above, parser 610 may not be able to parse the district from the address.

The longer match prefix locator 620 of geocoder 430 can be used to locate additional parts of the address. For example, the longest match prefix locator 620 may try to find the longest match prefixes (for example, bookmarks) from the address list. This may fail if there is no specific listing in the address book (for example, if "HeGang City" was not in the address book). The longer match prefix finder 620 may advance to the end of the word "City" if present in the address list. If an entire record (for example, "HeGang City AnLiang VillageAnLiang Road") is present in the address list, the longer match prefix locator 620 may identify the card as a good match (for example, "City of HeGang "can be identified as a good coincidence). The longest match prefix locator 620 may retry to find the longest match prefix (for example, token) from the address list. If it fails, then the longest match prefix finder 620 may advance to the end of the word " Village "if present (for example," AnLiang Village "). The longest match prefix finder 620 may repeat the process again to find the longest match prefix (e.g., token) from the address list. This time, the longer match prefix finder 620 may try to combine street names (for example, "Road" or "Street"). The longer matcher locator 620 may advance to the end of the "Road" or "Street" (s) if they are present (for example, "AnLiang Road"). The longer match prefix locator 620 may also advance to the end of the word "Number" if it is present (for example, "Number 172"). Finally, the longer match prefix locator 620 may attempt to locate the longest match prefix (e.g., record) from the POI name. This may provide coincidence for building names, schools, parks etc. (e.g., "JingCheng Building"). Combination Locator 630 can locate particular combinations so that POI names can be found first, then multiple-level-addresses ™, and finally districts or cities can be located. Such a location arrangement can ensure that the most specific address can be obtained by combining location 630. For example, combining locator 630 can find the following exemplary combinations: city + district + POI name; city + district + localized address by the finder

longer match prefixes 620 (e.g. "Road" or "Street");

city + district + address located by the longest match prefix finder 620 (e.g. "Village");

city + district + address located by the longest match prefix finder 620 (e.g. "City");

city + district; and / or city.

When a local search query is entered by a user, the location portion of the search query may be sent to a map server owned by a map provider. If the location action contains Chinese, Japanese, or Korean (CJK) characters, the map server can send this to question 640 geocoding unit for geocoding. If the user-entered location is ambiguous (for example, when the score of the first geocoder result is less than two times the score of the second result), the geocoding unit of question 640 may make suggestions to the user. For example, if the location question is "History Museum," the question 640 geocoding unit may provide the following suggestions for the user: "Do you want to look for the TianJian City He-Dong District History Museum or the Museum? PuDong District Shanghai History Museum? "The geocoding unit of question 640 can compute a search result's score based on the number of points in the search result's location. For example, if ChaoYang Town ChangChuanw District scores less than ChaoYang Town Beijing City, then ChaoYang Town Beijing City may be displayed when the location of the user question is "ChaoYang Town".

Although Figure 6 shows exemplary tasks performed by geocoder 430, in other embodiments, geocoder 430 can perform additional or different tasks that can be used to identify local search results. In addition, while Figure 6 shows geocoder 430 components as interconnected, in other implementations, geocoder 430 components may be separate, non-interconnected components.

Indexer

The indexer 435, as shown in Figure 7, can perform a variety of tasks to assist in identifying local search results. In one implementation, for example, indexer 435 may preprocess yellow page data 405 to determine business information (for example, address, telephone number, e-mail address, facsimile number, hours of operation, etc.) for POIs, you can extract business information from Web 410 document data and / or you can identify location information in a search query. The indexer 435 may include a map data indexer 700, a yellow page data preprocessor 710, a business information puller 720, a distance planner 730, a business breaker 740, a business information repository 750, a fragment 760 etc.

The indexer. of, map data 700 can. index, address data from map provider data 400, which may include map position information. Geocoder 430 may re-geocode the address based on indexed address data, and grouper 740 (described below) may adjust group position if group position is different from given position, but may not adjust group position above threshold of predetermined distance (eg within three kilometers). This arrangement can be used to improve grouping as described in detail below.

The yellow page data preprocessor 710 can receive yellow page data 405 from different printers and can preprocess yellow page data 405 to a common format. This formatted data may be provided to geocoder 430 during indexing and geocoder430 may attempt to geocod the address. If the address can be coded at the building or street level, the address can be indexed as a normal entry. If the address can be geocoded at the city or district level, the address can be indexed as an entry with an approximate position. During scoring, the input can be treated as if it were at least twenty kilometers from the centroid (ie essentially its score degraded). If the address cannot be geocoded, the address can be treated as an entry without a position. During indexing, if the entry without a position can be grouped with another entry (for example, using your phone number), the entry may be retained.

Otherwise, the entry may be discarded.

The Business Information Extractor 720 can extract business information (for example, addresses and telephone numbers) from 410 Web document data using a variety of techniques. Techniques can be modified based on the different formatting of addresses and telephone numbers in China and Japan.

For example, in a first technique, business information extractor 720 may include a classifier that can analyze address documents to determine business information associated with addresses based on a statistical model. Documents analyzed by the classifier may include address documents for which there is no corresponding data from yellow pages 405 and / or documents with addresses for which possibly incorrect data from yellow pages 405 exist. The functions performed by the classifier may differ based on whether business information matches business name information (title) or telephone number information. Still other functions may be performed when business information includes information other than business names or telephone number information. A business name (title) can be identified by analyzing terms close to the address and determining the likelihood that each term is part of the title. A confidence score can be assigned to each candidate title that is identified.

A telephone number can be associated with an address by identifying a set of candidate telephone numbers in the document. It can be determined on the basis of the statistical model that each candidate telephone number is associated with the address given the prediction relative to the preceding candidate telephone number and given a window of terms (for example by examining a predetermined number of terms left and / or right) around the candidate phone number. Confidence scores can be assigned to candidate phone numbers based on their determined odds. Optionally, you can determine the best phone number for the address. The telephone number can then be associated with the address to form a supplemental business listing.

In a second exemplary technique, business information extractor 720 may include a location extractor that may be included as part of the search engine. The location puller may receive a search query and determine if the search query includes a geographic reference. When the search question includes a geographic reference, the position puller can remove the geographical reference from the search terms in the question and submit them to a local search engine. Where the search query does not include a geographic reference, the location puller may submit the search terms to a web search engine that may include a traditional web search engine that returns a set of documents related to a search query. The local search engine may include a specialized search engine, such as a business listings search engine. In operation, the local search engine can receive the search terms and geographic reference of a search query from the location puller. The local search engine can identify a set of documents that combine the search query (ie documents that contain the search query set of search terms) by comparing the search terms with documents in a body of documents relating to the geographic area associated with the search. geographical reference. The local search engine can score identified documents, rank them based on their scores, and output them as a list of search results.

The location extractor can determine unambiguous addresses (e.g. cities) in a search query by setting a variable i equal to one and performing a search for a city name for each city (i) in a city list. The number of search results for this search can be counted as countcity. A search can also be performed for the city name with the corresponding province name. The number of search results for this search can be counted as countcity / province.

It can then be determined if countcity / province is at least X% (where X is a number greater than zero) of countcity. When countcity / province is at least X% of countcity, then city may be considered an "unambiguous city". " An "unambiguous citizen" may refer to a city whose name can be used on a search query and it will be understood that the user intended the city and not anything else. When count-city / province is not at least X% of countcity, then it can be determined if there are more cities in the list. If there are more cities in the list then variable i can be incremented by one and the next city in the list of cities can be evaluated.

Search result documents can be analyzed to identify any postal codes they contain. Postcodes can be identified using a pattern matching technique and verified by comparing them to a list of postcodes. It can then be determined whether the postcodes match the postcodes associated with the city (i). The number of documents containing postal codes associated with city (i) can be counted as countpostal. It can be determined if countpostal is at least X% (for example, 5%) of countcity. When countpostal is at least X% countcity, then the city can be considered an unambiguous city.

In a third exemplary technique, business information extractor 720 can identify a geographically relevant document. A geographically relevant document, as used here, can generally refer to any document that has been determined to have particular relevance to a geographical location. Business listings (for example, yellow page listings) can be considered a geographically relevant document that is relevant to the geographic region defined by the business addresses. Other documents, such as web documents, may also have particular geographic relevance. For example, a business may have a home page, may be the subject of a document that reviews or reviews business, or may be mentioned by a webpage that otherwise relates to business. The particular geographic location to which a business The associated document can be determined in various ways, such as from the address or other geographical signs.

The geographic region associated with the geographically relevant document can be mapped to a corresponding location identifier. Additional location identifiers can be determined for the document. In particular, location identifiers corresponding to the surrounding regions within a predetermined range may also be determined. Geographically relevant document can be indexed as if the document included the location identifiers associated with the document region as well as the surrounding identified regions.

Although Figure 7 shows the business information extractor 720 as part of the indexer 435, in other embodiments, the business information extractor 720 may be separate from the indexer 435. To ensure that the combination document set may be available in indexing, information extracted by the business information extractor 720 may be provided in the business information repository 750. The business information repository 750 may include a variety of information, for example, documents from which business information was extracted by the extractor 720 business information repository, along with extracted business information, can be provided within the 435 indexer. Although Figure 7 shows the business information repository 750 as part of the 435 indexer, in other implementations, the business information repository 7 50 may be separated from indexer 435.

The distance planner 730 can set a radius or search distance for a local search question. For example, in one embodiment, each local search query may be geocoded by geocoder 430 to a particular location. Each location can be a point location (eg buildings, famous statistic places, schools, street centers, etc.) or a limited location (eg districts, cities, provinces, etc.). For point locations, the distance planner 730 can set the search radius to a predetermined distance (for example, approximately five kilometers around the point). For limited locations, the distance planner 730 can set the striking radius to approximately the maximum distance from a centroid of position to corners. Results scores are debugged in a zcode set associated with the location (ie the set of tencodes that make up the position) can be promoted. Thus, when a user searches near a district name, the top results may be within that district.

Collator 740 may group map provider data 400 and yellow page data 405 together. Many data from map providers 400 may include accurate deposition information so that it can be accurately displayed on a map, but may not include detailed address or telephone number information (for example, it could include an address without a street number and / or missing a phone number). On the other hand, yellow page data 405 may include detailed address and telephone number information, but may not include accurate position information. For example, data from map providers 400 may include a source (for example, map provider), a title (for example, "Peking University"), an address (for example, "Beijing City HaiDian District YiHeYuan ") and / or a POI ID (for map display) (e.g." A1234567 "). However, yellow page data 405 may include an origin (eg, yellow page data provider), a title (eg "Peking University"), an address (eg "Beijing City HaiDian District YiHe Yuan Road Number 5 ") and / or a telephone number (e.g." 010-62752114 "). If these entries are grouped together by switch 740, then front end server 440 may be able to provide the user with detailed address and telephone number information as well as an accurate position on a map.

The position obtained from the geocoding (for example, with the geocoder 430) of the yellow page data address405 may be an approximation and may be far from the precise position provided by map provider data 400. In this case, the same business from two providers may be located in many different neighborhoods and thus may not be grouped together by cluster 740. The solution to this may include geocoding (for example, with geocoder 430) of the address from map provider data 400 through a group position. The group position can be used for neighborhood generation as well as for grouping by grouper 740. The actual position provided by data from the chip providers 400 can then be used to display the map.

The 760 fragment detacher can highlight document fragments (for example, web documents). Highlighting Web document fragmentation can typically be accomplished by misusing terms in documents. Since a CJK document may have terms counted differently from other languages (for example, using a space as a delimiter, a long paragraph of text may need to be segmented to get the terms), in order to highlight specific terms, the document The integer can be segmented to obtain matching terms, which can be inefficient. However, the 760 snippet detacher may store deviations instead of terms to identify an address and telephone number (or some other business information) in a Web document. during indexing. The 760 fragment detacher can use the shift offset to perform highlighting and no segmentation may be required. Although Figure 7 shows fragment detacher 760 as part of indexer 435, in other implementations, fragment detacher 760 may be detached from the dexterator and / or included in another component (e.g., front end server 440).

Although Figure 7 shows exemplary tasks performed by indexer 435, in other embodiments, indexer 435 may perform additional or different tasks that can be used to identify local search results. Moreover, while Figure 7 shows the indexer components 435 as interconnected, in other embodiments, the indexer components 435 may be separate, non-interconnected components.

Front End Server

Front End Server 440, as shown in Figure 8, can perform a variety of tasks to help identify local search results. In one embodiment, for example, front end server 440 may include a question rewriter 800, a local search generator 810, a map generator 820, a geographic information generator 830, and so on. Although Figure 8 shows exemplary tasks performed by Front End Server 440, in other implementations, Front End Server 440 can perform additional or different tasks that can be used to help identify local search results.

In one embodiment, issue rewriter 800 may perform a variety of tasks. For example, since the number of Web document groups may be much smaller for Chinese data compared to English data, a coincidence in a title or category may be used to return valid results. Also, in Chinese, there may be several synonyms that refer to same term. For example, the term "restaurant" may have several common Chinese synonyms. In addition, the different yellow page data providers 400 may use different names to represent the same category. In order to provide the biggest call to the user-entered search query, Question Rewriter 800 can generate a list of synonyms for each of the categories. Question rewriter 800 can also rewrite each local search query to expand the query to a pair of search terms that can be joined by an "OR" operator.

Local search generator 810 can generate local search results 450. For example, local search generator 810 can generate results corresponding to relevant web pages and / or business listings within a specific geographic area based on the address information obtained and processed by local search system 225. Local search results 450 may be displayed (for example, to the user entering the local search query) on a monitor (eg output device 370).

The map generator 820.png can generate a map relative to. _local search results 450. For example, in order to display the map for the results, the map generator 820 can construct a frame (i.e. a floating frame inserted into a web page) into the page search result and can perform an action. later to a URL provided by the map provider. The parameters in the post may contain the following fields for each search result: a title; an address; a telephone number; POI ID (to display the point on the map); and accuracy. Locations that can be geocoded to a building level can be marked as accurate on the map generator by map generator 820. Locations that can be geocoded to a street level (or some higher level of abstraction) can be marked as estimated by the map generator 820. Figure 9 illustrates how these two levels of accuracy can be distinguished on a map 900 generated from local search results 910. For example, precise locations 920 can be identified by a marker color. (e.g. green) and estimated positions 930 can be identified by another marker color (e.g. red). Although two levels of accuracy (accurate and estimated) are shown in Figure 9, additional levels of accuracy can be used in other embodiments consistent with the principles of the invention.

During indexing by the indexer 435, the fingerprint of the address (e.g., FP address 540) can be stored along with its associated accuracy (e.g., accuracy ofFP 550). Mapping between the address fingerprint and the POI ID (for example, address FP / POI ID 425 mapping information) can be used by map generator 820 to search the POI ID for each search result. The POI ID can be used by map generator 820 to identify a map position (eg map 900) for the map provider, so that the map provider can show the map position provided within the result page.

In order to display local advertisements for China, the 830 geographic information generator can provide geographic information for the 840 ad server in a variety of ways. For example, in one implementation, each self-administered province or city may have a two-digit code, which may be the second part of the region code defined by ISO-3166-2. Geocoder 430 can index this code (for example, "CN-dd") with each address and pass it to front end server 440 for each successful geocoded address. The 830 geo generator can send code to ad server 840 as a region geocode.

In another implementation, advertisers may offer keyword overlays from <keyword, position> instead of using geotargeting, because for web searches geotargeting may not work as well in Asian countries as it does in the United States. for ads may be more for these keyword pairs. As a result, the 830 Geo Info Generator can reconcile keywords with the positions entered by the search question and can use these concatenations as keywords sent to the 840 ad server. For example, when the user searches for "restaurant" near "Beijing ", the keyword sent to ad server 840 by geographic information generator 830 may be" Beijing restaurant. " This provision can be provided for both Japan and China.

In yet another implementation, the geographic information generator 830 can determine whether the search question includes a geographic reference. If the search question does not include a geographic reference, then regular ads may be displayed by the 840 ad server. However, it can be determined whether a user position indicator, such as the user's IP address, is available. When a user position indicator is available then local ads may be displayed based on the user's location.

If, on the other hand, the search question includes a geographic reference, then the geographic information generator 830 can determine whether the geographic reference corresponds only to a city name (ie without any other geographic information such as no provincial information). If the search question includes a geo-reference other than just a city name, then local ads may appear.

If the search question includes a geographic reference that corresponds to only one city name, then the geographic information generator 830 can determine if the city corresponds to an unambiguous city. If the city does not match an unambiguous citizen, then regular ads may appear. If the city corresponds to an unambiguous city, then the geographic information generator 830 can determine whether the common city name or more other query search terms appear in a blacklist. A blacklist can be kept for unambiguous city names that, when combined with one or more words, mean something different from their respective cities. If the common city name or more other search terms of the question are blacklisted then regular ads may appear. If the name dacity with one or more other query search terms does not appear on the blacklist, then local ads may be displayed based on the geographic reference of the query.

If local ("targeted") ads are to be displayed, user location information (for example, the user's IP address) may be used by the geographic information generator 830 to determine if the location is within a predetermined distance from the location corresponding to the location. geographical reference. If the user's location is within the predetermined distance, then local ads may appear. If the user's affix is out of the predetermined distance, however, then regular advertisements may appear.

Front End Server 440 (or components of Front End Server 440) can perform some tasks that may be specific to China. For example, the 440 front end server can hide direction directions, provide a country dependent display unit (mile per mile), filter for sensitive keywords when in China, provide specific address and number formatting phone numbers for display, show the geocoded location at the top of the map, and / or round the distance to 0.5 kilometers instead of 0.1 kilometers and remove the direction.

Example Process

IOA-IOD Figures are flowcharts of an exemplary process for identifying local search results and providing a map associated with identified positions.

Locale Search Result Exemplary Map Generation Process

As shown in Figure 10A, a process 1000 for identifying local search results and providing a map associated with identified locations can start with receipt of the yellow pages, map provider and document data (block 1005). For example, in an embodiment described above with respect to Figure 4, map provider data 400, yellow page data 405, and web document data 410 may be provided for indexer 435, and map provider data 400 may further be used to derive ID data from POI / Address and Address FP Mapping Information / POI ID 425.

Process 1000 can perform geocoding over data (block 1010). For example, in an implementation described above with respect to Figure 6, the address book generator 600 of the geo-jammer 430 can receive data from map providers 400 and data from yellow pages 405 and can generate an address list based on provinces, cities, districts, street names, addresses, POI names, or combinations thereof from map provider data 400 and / or yellow page data 405. Analyzer 610 from encoder 430 can attempt to analyze the city and / or district from the beginning of each Address. Longer match prefix locator 620 of geocoder 430 can be used to locate additional parts of each address. The geocoder's combination finder 630 can locate particular combinations so that POI names can be located first, then multiple levels of addresses can be located, and finally districts or cities can be located. The geocoding unit of question 640 of geocoder 430 can compute a search result score based on the number of points in the search result location.

As best shown in Figure 10A, process 1000 can perform indexing on data (block 1015). For example, in an implementation described above with respect to Figure 7, the map data indexer 700 of indexer 435 may index address data from map provider data 400, which may include map position information. The yellow page data preprocessor 710 of indexer 435 can receive yellow page data 405 from the different providers and can preprocess yellow page data 405 to a common format. The business information extractor 720 from indexer 435 can extract business information (for example, addresses and telephone numbers) from web document data 410 using a variety of techniques. Techniques can be modified based on the different formatting of addresses and phone numbers in China and Japan. The extracted business information can be provided in the business information repository 750. The distance planner 730 of indexer 435 can set a search radius for a local debauchery issue. Indexer 440 740 can group map map data 400 and yellow page data 405 together. The 760 shard detacher of indexer 435 can highlight fragments in documents (for example, web documents).

Process 1000 can generate local search results and can provide a map URL (block 1020). For example, in an implementation described above with respect to Figure 8, the front end server local search generator 810 440 may generate local search results 450 (e.g., relevant web pages and / or business listings within a specific geographic area, with address information obtained and processed by the local search system 225). Front end server map generator 820 can generate a map relative to local search results 450. For example, in order to display the map for results, map generator 820 can construct a frame i (i.e. a floating frame within a webpage) over the search results page, and you can take further action to a URL provided by the map provider.

Exemplary Geocoding Process

Process block 1010 (Figure 10A) of process 1000 may include the blocks shown in Figure 10B. Thus, process block 1010 can generate an address list (block 1025). For example, in an embodiment described above with respect to Figure 6, the address book generator 600 of geocoder 430 can receive data from map providers 400 and yellow page data 405e can generate an address book based on provinces, cities, districts, street names, addresses, POI names or combinations thereof from map provider data 400 and / or yellow page data 405. Process block 1010 can analyze each address in the address list (block 1030) . For example, in an implementation described above with respect to Figure 6, for each address, parser 610 of geocoder 430 may attempt to parse the address and district of address.

As further shown in Figure 10B, process block 1010 can find the longest match prefixes from each address in the address list (block 1035). For example, in a embodiment described above with respect to Figure 6, longer match prefix locator 620 of geocoder 430 may be used to locate additional parts of the address (e.g., a city, a village, a road or street, number, If the longer comparison prefixes are not found in the address (block 1040 - NO), then process block 1010 may continue to find additional parts of the address (block 1035).

If the longest comparison prefixes are located at address (block 1040 - YES), then process block 1010 can find combinations of each address (block 1045). For example, in an implementation described above with respect to Figure 6, the geocoder 430 combination locator 630 can locate particular combinations so that first POI names can be located, then multiple levels of addresses and locations can be located. Finally, districts or cities can be located. Such a locator arrangement can guarantee or verify that the most specific address possible can be obtained by the combination locator 630.

Exemplary Indexing Process

Process block 1015 (Figure 10A) of process 1000 may include the blocks shown in Figure 10C. In this way, process block 1015 can preprocess the yellow page data (block 1050). For example, in an implementation described above with respect to Figure 7, the yellow page data preprocessor 710 of indexer 435 may receive yellow page data 405 from different providers and may preprocess yellow page data 405 to a common format ( or predetermined). This formatted data can be supplied to geocoder 430 during indexing and geocode 430 can attempt to geocode address. If the address can be geocoded at the gold building level, the address can be indexed as a normal entry. If the address can be geocoded at the city or district level, the address can be indexed as an entry with an approximate position.

Process block 1015 can extract business information from documents (block 1055) and can store business information (block 1060). For example, in an implementation described above with respect to Figure 7, the business information extractor 720 of indexer 435 can extract business information (e.g., addresses and telephone numbers) from Web document data 410 using a variety of techniques. Techniques may be modified based on different formatting of addresses and telephone numbers in China and Japan. In another implementation described above with respect to Figure 7, extracted business information may be provided in the information repository of business750. The business information repository 750 may include a variety of information, for example, documents from which business information was extracted by the business information extractor 720.

Process block 1015 can index address data received from a map provider (block 1065). For example, in a embodiment described above with respect to Figure 7, the map data indexer 700 of indexer 435 may index address data from map provider data 400, which may include map position information. Geocoder 430 may attempt to re-encode the address based on the dexposed address data, and grouper 740 may set the group position if the group position is different from the given position, but may not set the group position above a limit. predetermined distance (eg within 3 kilometers).

As further shown in Figure 10C, process block 1015 can group yellow page data and map provider data (block 1070). For example, in one embodiment described above with respect to Figure 7, cluster 740 of indexer 435 may group map provider data 400 and yellow page data 405 together. If these entries are grouped together by switch 740, then the front end server. 440 may be able to provide the user with detailed address and telephone number information as well as an accurate position on a map.

Process block 1015 may detach fragments provided in documents (block 1075). For example, in an implementation described above with respect to Figure 7, the fragment detacher 760 of indexer 435 may detach fragments in documents (for example, web documents). Snippet 760 can store shifters rather than term shifts to identify an address or phone number (or some other business information) in a web document during indexing. Snippet 760 can use shifters to perform highlights and no segmentation may be required.

As further shown in Figure 10C, process block 1015 can set a seek distance (block 1080). For example, in an embodiment described above with respect to Figure 7, the distance planner 730 of indexer 435 may configure a lightning bolt for a geocoded local search question by geocoder 430 for a particular location. Each location can be a point location (eg buildings, famous tourist sites, schools, street centers, etc.) or a limited location (eg districts, cities, provinces, etc.). For point locations, the distance planner 730 can set the search radius to a predetermined distance (e.g., approximately five kilometers around the point). For limited locations, the distance planner 730 can set the search radius to approximately the maximum distance from a centroid of the location to the corners.

Example Process

of the front end server

Process block 1020 (Figure 10A) of process 1000 may include the blocks shown in Figure 10D. Thus, process block 1020 may rewrite a search query (block 1085). For example, in an implementation described above with respect to Figure 8, there may be several synonyms that refer to the same Chinese term. In addition, the different Yellow Page 400 data providers may use different names to represent the same category. In order to provide the largest call to the user-entered query question, the front end server question rewriter 800 can generate a list of synonyms for each of the categories. The 800 question rewrite can also rewrite local search query which can expand the query to a search terms that can be joined by an "OR" operator.

Process block 1020 can generate local search results based on the search query and can generate a map showing search result locations (block 1090). For example, in an implementation described above with respect to Figure 8, front end server local search generator 810 440 may generate local search results (e.g., web pages and / or relevant business listings within an area). specific address information obtained and processed by the local debugging system 225). In another embodiment described in relation to Figure 8, the front end server 440 map generator 820 may generate a map relative to the local search results 450. For example, in order to display the map for the results, the map generator 820 may - construct an i frame (i.e. a floating frame within a webpage) over the search results page and you can perform a further action to a URL provided by the map provider. The POI ID can be used by the map generator 820 to identify a position on CvTnapa (eg map 900) for the map provider so that the map provider can show the map position provided within the results page.

As further shown in Figure 10D, process block 1020 can generate geographic information for an ad server (block 1095). For example, in one embodiment described above with respect to Figure 8, in order to display local advertisements for China, the front-end server geographic information generator 830 may provide geographic information for the ad server840. For example, the geographic information generator 830 might send region code to ad server 840 as a region code. In another example, the geographic information generator 830 may concatenate keywords with the positions entered by the user's search query entry and may use these concatenations as the keywords sent to the ad server 840.

Conclusion

The implementations described herein may provide systems and methods for identifying local search results and generating a map associated with the identified locations. The system may receive a local search query entry by the user and may identify a position associated with the local search query. The system may identify a set of local search results that may be related to the local search issue and may be associated with the identified location. Local search results may include links to documents that may relate to the local search query. The system can identify an identifier for a group of local search results and can provide the identifier for a map provider. The system may receive a map associated with an identified location from the map provider. The map can identify a position of at least one search result in the local search result group.

The described embodiments provide one or more of the following advantages. For example, map data and yellow page data can be used from different providers to identify local search results and generate an associated map with identified locations. The map can be conveniently displayed with local search results. This arrangement prevents the generation of local search results and a pointer to a third-party map provider server.

In another example, the map may provide detailed map data based on the yellow page data ...: This may. make it possible to generate a map that includes detailed map data in countries where export restrictions may limit the availability of detailed map data to deliver the map or may limit the availability of actual address latitude and longitude within the area.

The foregoing description of embodiments of the present invention provides illustration and description, but is not intended to be exhaustive or to limit the invention to the precise form disclosed. Modifications and variations are possible taking into account the above teachings or may be acquired from the practice of the invention. For example, although series of acts have been described with respect to Figures 10A-10D, the order of acts may be modified in other implementations consistent with the principles of the invention. In addition, nondependent acts may be performed in parallel. In one implementation, server 220 may perform most, if not all, of the acts described with respect to processing of the IQA-10D Figures. In another implementation, one or more or all of them may be performed by another entity, such as another server 230e and / or 240 or client 210.

In another example, alternative approaches may be used for geocoding addresses that are not provided by the map provider. In an alternative approach, the 430 geocoder may attempt to locate the nearest point of an address to be geocoded. For example, suppose that the points "1 ABC Street" and "10 ABC Street" are identified by the map provider. When attempting to encode the "3 ABC Street" address, geocoder 430 may return the location "1 ABC Street", which is the closest point to "3 ABC Street". In another alternative approach, geocoder 430 may attempt to interpolate a point. For example, if "1 ABC Street" is at the gradation index (0, 0) and "10 ABC Street" is at the grid index (10, 20), geo-430 might determine that the address of "3 ABC Street" "is in the grid index (3, 6) based on interpolation. Still in another example, alternative approaches can be used to obtain the POI ID for drawing the map. In an alternate approach, the POI ID can be stored with location data from the map provider. POI IDs may be returned by Front End Server 440 during service time. POI IDs may change in different versions of map depraving data. Storing the POI ID in the index makes the index dependent on the data from the map provider. In another alternative approach, search result addresses may be geocoded during service time and geocoder 430 may be required to provide the nearest comparison points. The 430 encoder can return the point POI IDs. Requests from the nearest comparison points can be sent in batches (for example, lots of ten) of geocoding requests so that the performance impact can be small.

In a further example, while systems and methods are described in terms of a Chinese local search, in another implementation, some of the techniques described herein may apply equally to local searches in other countries.

It will be evident to a person of ordinary ability in the

It is understood that aspects of the invention as described above may be implemented in many different ways in software, firmware and hardware in the embodiments illustrated in the Figures. The actual software code or specialized control hardware used to implement aspects consistent with the principles of the invention are not limiting of the invention. Thus, the operation and behavior of aspects were described without reference to the specific software code - it being understood that a person of ordinary skill in the art would be able to design control software and hardware to implement the aspects based on the present description.

No element, act, or instruction used in the present application shall be construed as critical or essential to the invention unless explicitly described as such. Also, as used herein, article "one" is intended to include one or more items. In cases where only one item is intended, the term "one" or similar language is used. In addition, the phrase "based" is intended to mean "based, at least in part, on" unless explicitly stated otherwise.

Claims (46)

1. Local Search Method, comprising: receiving yellow page data, third-party map provider data, and document data in response to a local search question, geocoding at least one of the page data to love them, the data third-party map provider and document data to assign a geographic identifier and match at least one address within the local search query; index geocoded data to identify business information and location information matching the local search query ; and provide local search results and a third-party map based on identified business and location information. Local Search Method according to Claim 1, characterized in that the yellow page data comprises at least one POI address, POI telephone number information, a business name, a email address, facsimile number, Network website address, CEO name, business description, SIC style category, or business type. Local Search Method according to Claim 1, characterized in that the data from the third-party map provider comprises a point of interest (POI) and a POI address. Local Search Method according to Claim 3, characterized in that the third-party map provider data further comprises a grid for the POL. Local Search Method according to Claim 1, characterized in that the third-party map provider data comprises at least one of: a normal point of interest (POI) that includes a business name, an address, a telephone and grid index, a POI road that includes a street name and a street center degrade index, or a POI zip code that includes a zip code and a grid index of an approximate center of the zip code. Local Search Method according to Claim 1, characterized in that the geocoding comprises: generating an address list based on the local search question, parsing each address in the address list, locating the longest match prefixes in each address to identify parts of each address; Find combinations in each address to verify each address. 7. Local Search Method according to Claim 1, characterized in that the indexing comprises: preprocessing yellow page data to a predetermined format, extracting business information from document data, indexing address information from third party map provider data; and group the yellow page data and third-party map provider data. 8. Local Search Method according to Claim 7, characterized in that the indexing further comprises: storing business information in a repository, highlighting fragments in document data; and set a search distance for the local search issue. Local Search Method according to Claim 1, characterized in that the supply comprises: generating a list of synonyms related to the local search question, rewriting the local search question to expand the issue, generating the search results. local search based on the expanded question; get the third-party map based on local search results; and generate ads based on geographic information related to local search results. Local Search Method according to Claim 1, characterized in that the location information is determined from third-party map provider data and yellow page data. Geocoding method, based on a local search query, characterized by: receiving data from the third-party map provider and yellow page data, generating an address based on the local search query, analyzing the address, locating match prefixes longer addresses to identify at least part of the address; Find a match in the address to verify the address. Geocoding method according to Claim 11, further comprising: generating the address based on information included in third-party map provider data or yellow page data. Geocoding method according to Claim 11, further comprising: analyzing a city and a district of the address. Geocoding method according to Claim 11, characterized in that the address portion comprises at least one of a city, a village, a road, a street, a number or a name of a point of interest. 15. The geocoding method of Claim 11 further comprising: locating the combination at the address such that a point of interest name is located first, other parts of the address are located second, and a district or city is located third. 16. A geocoding method according to Claim 11, further comprising: indexing the address as an exact position if the address includes a building or part of a street. Geocoding method according to Claim 11, further comprising: Indexing the address to an approximate position if the address includes a part of the city or a part of a district. 18. Indexing method, based on a local search query, comprising: preprocessing yellow page data to a predefined format; extracting business information from document data; storing the information index address information from third-party map provider data; group yellow page data and third-party map provider data; highlight fragments in document data; for a point location, set up a distance searches for the local search question for a predetermined distance; and for a limited location, set the debus distance to approximately a maximum distance from a centroid of the limited location to the corners of the limited location. An indexing method according to claim 18 further comprising: preprocessing the yellow page data to a predetermined format. Indexing method according to Claim 18, characterized in that the business information comprises at least one of a business address or business phone number. The Indexing Method of Claim 20 further comprising: modifying the extraction of business information based on business address format differences or business telephone number. Indexing method according to Claim 18, further comprising: storing documents associated with business information in the repository. Indexing method according to Claim 18, further comprising: geocoding an address based on the indexed address information; and determine a new grouping position based on the geocoded address. if the new grouping position is different from a previous grouping position. Indexing method according to Claim 18, characterized in that it further comprises: detaching the fragments in the document data based on the deviations of baites that are stored to identify the business information in the document data. 25. Local Search Method, comprising: generating a list of synonyms related to a local search query, rewriting the local search query to expand the search, generating local search results based on the expanded query, obtaining a map from a third-party map provider based on local search results; and generate ads based on geographic information related to local search results. Local Search Method according to Claim 25, further comprising: rewriting the local search question by joining search terms with an "OR" operator. A Local Search Method according to Claim 25, characterized in that obtaining the map comprises: constructing a map frame with the local search results, performing a post action for a URL provided by a third party map provider; and identify a position on the map in order to enable the third-party map operator to show the position on the map. 28. A local search method according to claim 25, further comprising: generating advertisements based on a region code relating to the local search results. 29. A local search method according to Claim 25, further comprising: concatenating a keyword with a position related to the local search query; egenerate ads based on the concatenated keyword. 30. - Local Search System, comprising: an indexer for receiving third-party map provider data, yellow page data and document data, preprocessing yellow page data to determine business information, extracting business information from document data, identify location information in a local search query and index address data from third-party map provider data, a geocoding for receiving information from the indexer and assigning geographical identifiers; It is a front-facing server for receiving information from the encoder, rewriting the local search query, obtaining a map from third-party map provider data, and generating local search results based on the local search query. Local Search System according to Claim 30, further comprising: an index / document repository storing at least one of the address data provided by third-party map provider data, points of interest information, centers postal codes or cities not included in third-party map provider data. Local Search System according to Claim 30, characterized in that the indexer preprocesses the yellow page data to a predetermined format. Local Search System according to Claim 30, characterized in that the indexer sets a search distance for local search query. Local Search System according to Claim 30, characterized in that the indexer groups the third-party map provider data and the yellow page data. Local Search System according to Claim 30, characterized in that the indexer highlights fragments in the document data. Local Search System according to Claim 30, characterized in that the geocoder receives third-party map provider data and yellow page data and generates a mailing list from third-party map provider data and data. of the yellow pages. Local Search System according to Claim 30, characterized in that the geocoder locates parts of an address. 38. Local Search System according to Claim 37, characterized in that the geocoder finds combinations within the address. Local Search System according to Claim 30, characterized in that the geocoder computes local search result scores based on various points at a search result location. 40. Local Search System according to Claim 30, characterized in that the front-end server generates a list of synonyms related to the local search question. 41. Local Search System according to Claim 30, characterized in that the front server generates an estimated location and an exact map location for at least one local search result. 42. Local Search System according to Claim 30, characterized in that the front end server generates advertisements based on geographic information related to the local search results. 43. A local search system, comprising: means for receiving yellow page data, third-party map provider data and document data in response to a local search question; means for geocoding at least one of the yellow page data , third-party map provider data and document data for assigning a geographic identifier and combining at least one address within the local search query, means of indexing geocoded data to identify business information and location information. corresponding to the local search issue; means to provide local search results and a third-party map based on identified business and location information. 44. A local search system comprising: a memory for storing a plurality of instructions; and a processor for executing instructions in memory to: identify a location associated with a local search query, identify local search results relevant to the local search query and associated with the identified position, identify an identifier for each of a group of local search results and receive from a third-party map provider a map associated with the identified position, where the map identifies a position of at least one local search result in the local search result group. 45. Local Search Method, comprising: receiving a local search question, identifying a position associated with the local search question, identifying a set of search results relevant to the local search question and associated with the identified location; identify an identifier for each of a search result group, provide an identifier for each of the search results group to a third party map provider; get from the third-party map provider a map associated with the identified location, where the map identifies a position of at least one search result in the search results group. 46. Local Search Method, comprising: generating a token list; identify a potential address in a Network document; analyze the potential address from the beginning to determine if the potential address includes a token associated with a city; further analyze the potential address to determine if the potential address includes a token associated with a district; longer match form at the potential address after the form associated with the city or the form associated with the district; Determine if the potential address is a real address based on the token associated with the city, the token associated with the district, and the longest identified token.