KR101556743B1 - Apparatus and method for generating poi information based on web collection - Google Patents

Abstract

An apparatus for generating point-of-interest (POI) information based on web collection includes: a POI information index DB which stores index information of POI information categorized by each ID; a collection unit which collects web data from a plurality of web sites; an extraction unit which extracts POI information from the web data collected by the collection unit; a mapping unit which maps web data, including the extracted POI information, with an obtained ID if obtaining the ID, mapped with the POI information extracted by the extraction unit, from the POI index DB; and a mapping database which stores a mapping relation between the web data and the obtained ID. During a search for the POI information upon user′s request, the web data, mapped with the ID of the POI information, are also searched.

Description

[0001] APPARATUS AND METHOD FOR GENERATING POINT INFORMATION BASED ON WEB COLLECTION [0002]

The present invention relates to an apparatus and method for generating interest information based on web collection.

Point of Interest (POI) refers to data that is displayed on an electronic map with coordinates of major facilities, stations, airports, terminals, hotels, and so on.

Conventionally, in order to acquire meta data of interest information (POI), first, a DB containing a business name, an address, and a telephone number should be referred to. However, collection of domain-dependent metadata other than business name, address, and telephone number is not provided in DB. Therefore, it is necessary to manually rely on the method of collecting map information by directly visiting the site, which consumes manpower and cost. In addition, there is a problem that it is not easy to provide services at an appropriate time because it is difficult to cope with rapidly changing period of interest information (POI) because the correspondence of interest information (POI) which changes every moment is inevitably late.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide an apparatus and method for generating interest information based on web collection, which can automatically extract meta information related to POI from web data and database it.

According to an aspect of the present invention, an apparatus for generating interest information based on web collection includes a POI index DB for storing index information of interest information (POI) classified by ID, (POI) extracted from the web data collected by the collecting unit, and an ID mapped to the interest information (POI) extracted by the extracting unit, A mapping unit for mapping the web data including the extracted interest information to the obtained ID when acquired from the DB, and a mapping database for storing a mapping relation between the web data and the acquired ID,

The web data mapped to the ID of the POI may be searched together with the search for POI according to a user request.

The web site provides an environment in which a user can upload a post according to his / her interests,

Each of the web data may include articles registered by the user according to his / her interests.

Wherein,

A collection module for filtering and extracting web data corresponding to a title, a body, a URL (Uniform Resource Locator), a collection date, a creation date, and a map from the collected web data; And a DB management module for storing the data in a database.

Wherein the acquisition module comprises:

The web data can be collected, filtered, and extracted according to a web collection setting function preset by a user including a collection target URL, a collection link pattern setting, and a collection field pattern.

Wherein,

An image parsing module for extracting an image tag URL and storing the image tag URL in the mapping database through the DB management module when the image tag is included in the collected web data, As shown in FIG.

The image parsing module comprising:

A value indicating an image URL extraction may be set in the image flag of the mapping database.

Further comprising a determination unit for determining whether the web data collected by the collection unit is included in a predefined category,

The extracting unit extracts,

The POI may be extracted from web data included in the predefined category.

Wherein,

If the category is included in the predefined category, the category flag of the mapping database is set as the inclusion value. If the category flag is not included in the predefined category, the category flag may be set as the inclusion value.

The extracting unit extracts,

A preprocessing module which preprocesses the texts included in the main body of the web data stored in the mapping database on a line basis and lists only nouns except for auxiliary words or surrogates for the arranged texts, And an extraction module for tagging the telephone number.

Wherein the extraction module comprises:

After the tagging process, a value indicating the extraction of the POI may be set in the POI flag.

Wherein the mapping unit comprises:

An address code conversion module for converting the tagged phone number into a POI data format and converting the address into a PNU code format, and a POI index Retrieves the DB, obtains the ID of the POI corresponding to the converted telephone number and address, maps the acquired ID to the converted web address and the extracted web address, and stores the ID in the mapping database Mapping module.

Wherein the mapping module comprises:

Upon acquiring the ID of the POI corresponding to the converted telephone number and address, a value indicating the ID acquisition may be set in the POI flag.

In addition, the interest information generation apparatus may further include a mapping management unit for providing an interface through which the user can manage the mapping web data details.

According to another aspect of the present invention, a method for generating POI based on web collection is a method for generating POI based on web collection, (POI) generating apparatus collects respective web data from a plurality of web sites, acquiring an ID mapped to interest information (POI) extracted from the web data from a POI index database, Mapping the web data including the extracted interest information to the POI and retrieving the web data mapped to the ID of the POI when retrieving POI according to a user request.

Wherein the collecting comprises:

Filtering and extracting web data corresponding to a title, a text, a Uniform Resource Locator (URL), a collection date, a creation date, and a map from the collected web data; determining whether the web data is included in a predefined category And extracting the POI including the address and the telephone number from the body of the extracted web data if the category is included in the predefined category.

Wherein the collecting comprises:

And if the collected web data includes an image tag, extracting the image tag URL and displaying the extracted image tag advertisement at the image location and the body text.

The step of extracting the POI (POI)

Performing a preprocessing of arranging the texts included in the main text line by line and listing only nouns excluding the auxiliary verbs or the search for the arranged texts and tagging the addresses and telephone numbers of the preprocessed texts can do.

Wherein the mapping comprises:

Converting the tagged phone number into a POI data format, converting the address to a PNU code format, searching the POI index database using the converted phone number and address as keywords, Obtaining an ID of interest information (POI) corresponding to the converted telephone number and address, and mapping the obtained ID to the extracted web number and the converted telephone number and address.

According to the embodiment of the present invention, unstructured text of web data collected from a domain of interest is structured to automatically extract various types of POI-related meta information and DB, ) It is possible to keep various information in up-to-date state in conjunction with DB.

FIG. 1 is a block diagram illustrating a configuration of an interest information generation apparatus based on web collection according to an embodiment of the present invention. Referring to FIG.
FIG. 2 is a flowchart illustrating a series of processes for generating interest information based on web collection according to an embodiment of the present invention.
3 is a block diagram showing a detailed configuration of the collecting unit of FIG.
Figure 4 is a flow diagram illustrating operation according to one embodiment of the collector of Figure 3;
FIG. 5 is a flowchart showing an operation according to another embodiment of the collecting unit of FIG. 3; FIG.
6 is a block diagram showing the detailed configuration of the determination unit of FIG.
7 is a flowchart showing the operation of the determination unit of FIG.
8 is a block diagram showing a detailed configuration of the extracting unit of FIG.
9 is a flowchart showing the operation of the extracting unit of FIG.
10 is a block diagram showing the detailed configuration of the mapping unit of FIG.
11 is a flowchart showing the operation of the mapping unit of FIG.
12 is a block diagram showing the detailed configuration of the mapping management unit of FIG.
13 is a schematic diagram of a device for generating interest information based on web collection according to another embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when an element is referred to as "comprising ", it means that it can include other elements as well, without excluding other elements unless specifically stated otherwise.

Also, the terms of " part ", "... module" in the description mean units for processing at least one function or operation, which may be implemented by hardware or software or a combination of hardware and software.

Hereinafter, a POI (point of interest) generation apparatus and method based on web collection according to an embodiment of the present invention will be described in detail with reference to the drawings.

The interest information generation apparatus based on the web collection according to the embodiment of the present invention can automatically extract the interest information (POI) related metadata by mining a web page, etc. and register the extracted interest information (POI) Search, and recommendation services.

1 is a block diagram illustrating a configuration of a POI generation apparatus based on web collection according to an embodiment of the present invention.

1, a POI generating apparatus 1 includes a collecting unit 100, a mapping database 200, a determining unit 300, an extracting unit 400, a mapping unit 500, (POI) database 600 and a mapping management unit 700.

Here, the collecting unit 100, the determining unit 300, the extracting unit 400, the mapping unit 500, and the mapping management unit 700 may be implemented in a single processor (not shown) , A central processing unit (CPU) or other chipset, a microprocessor, or the like.

In addition, although the POI generating apparatus 1 is described as being implemented as one component, it may be implemented as a separate server. In this case, the collection unit 100 and the mapping management unit 700 may be implemented in one server. In addition, the determination unit 300, the extraction unit 400, and the mapping unit 500 may be implemented as a single server and implemented as a semantic server.

Then, each component will be described as follows. The collecting unit 100 collects respective web data from a plurality of web sites. Here, the web site provides an environment in which the user can upload articles according to his / her interests, and each web data includes articles registered by the user in accordance with his / her interests. For example, web data may include blog data.

The mapping database 200 stores web data collected by the collecting unit 100. It also stores the mapping relationship between the web data and the POI ID. In addition, a plurality of flags to be described later are stored.

The determination unit 300 determines whether the web data collected by the collection unit 100 is included in a predefined category. Here, the category may be set as a restaurant blog, and it can be determined whether the collected web data is restaurant-related data.

The extracting unit 400 extracts interest information (POI) from the web data collected by the collecting unit 100. Here, the POI may include an address and a telephone number.

The mapping unit 500 acquires interest information extracted from the interest information (POI) ID 600 obtained from the interest information (POI) index DB 600, which is mapped to the interest information (POI) extracted by the extracting unit 400 Map the included web data.

The interest information (POI) index DB 600 stores index information of interest information (POI) classified by ID. Then, the mapping database 200 and the interest information (POI) index DB 600 are interlocked with each other and the web data mapped to the ID of the interest information (POI) is searched together with the interest information (POI) search according to the user request have.

The mapping management unit 700 provides an interface through which the user can manage the mapping web data details.

FIG. 2 is a flowchart illustrating a series of steps of a method for generating interest information based on web collection according to an embodiment of the present invention. Referring to FIG.

Referring to FIG. 2, the collecting unit 100 collects respective pieces of web data from a plurality of different web sites (S101).

The collecting unit 100 extracts only predefined web information from the web data collected in step S101 and stores it in the mapping database 200 (S103).

At this time, the collecting unit 100 determines whether the URL (Uniform Resource Locator) is included in the predefined web information (S105).

If the image URL is included, the collecting unit 101 sets the image flag IMG_FLAG of the mapping database 200 to '1' (S107). At this time, the initial value of the image flag IMG_FLAG is set to '0'.

Next, the determination unit 300 determines whether the web information extracted in step S103 belongs to a predefined category (S109). For example, a restaurant blog.

If it is determined that the category flag belongs to the predefined category, the category flag is set to '1' (S111). If it is determined that the category flag does not belong to the predefined category, the category flag is set to '-1' )do.

The extraction unit 400 extracts interest information POI from the web information extracted in step S103 and sets the interest information flag POI DATA FLAG to '1' (step S117). Here, the POI includes an address and a telephone number.

The mapping unit 500 converts the interest information POI extracted by the extraction unit 400 into a PNU code and then converts the interest information POI corresponding to the converted interest information POI into a POI index (S121), and updates the interest information flag (POI DATA FLAG) to '2' (S123). Here, the PNU code includes a code (one digit), a main code (four digits), a code (three digits), an area code (three digits) , And an access code (4 digits).

In step S127, the mapping unit 500 maps the interest information ID (POI ID) acquired in step S121 to the web information extracted in step S103 (S125) and registers it in the mapping database 200 (S127).

In this way, it is possible to map and store the blog information in the POI using addresses and phone numbers extracted from Naver, Daum, Nate, and Taste's blog. In particular, in the case of a restaurant, the reliability problem is solved by collecting the metadata such as business name, business type, menu, business hours, other information, and reputation, and additional information such as user preference, ranking, (POI).

Hereinafter, the configuration described with reference to FIGS. 1 and 2 will be described in more detail.

FIG. 3 is a block diagram showing the detailed configuration of the collecting unit in FIG. 1, FIG. 4 is a flowchart showing an operation according to an embodiment of the collecting unit in FIG. 3, and FIG. 5 is a flowchart illustrating an operation according to another embodiment of the collecting unit in FIG. Fig.

3, the collecting unit 100 includes a collecting module 110, an image parsing module 120, a DB management module 130, a procedure 140, and an integration agent 150. [

The collection module 110 filters and extracts web data corresponding to title, body, URL, collection date, creation date, and guidance from the collected web data.

At this time, the collection module 110 collects, filters, and extracts web data according to a web collection setting function preset by the user including the collection target URL, the collection link pattern setting, and the collection field pattern.

Specifically, the web collection setting function includes setting a target URL to be collected, setting a collection link pattern, and setting a field pattern to be extracted from the collected Html page.

Here, the collection field includes a field item to be extracted from the collected web data (including an HTML page), and the field item includes a title, a body text, a collection URL, a map date, and a creation date.

The collection module 110 may periodically check the collection status, for example, execute a collection completion check script (Script) every 5 minutes.

When the image tag is included in the collected web data, the image parsing module 120 extracts the image tag URL and stores it in the mapping database 200 through the DB management module 130. And displays the extracted text tag text extracted by the filtering module 110 and the image tag extracted at the image position.

That is, the image parsing module 120 extracts the contents (image URL) of the image tag from among the contents of the file generated in the SCD folder at the time of collection and stores it in the mapping database 200. Then, using the file, the text corresponding to the text and the image is displayed in the text in the same way as the image commercial extraction. For example, the following Table 1 shows.

Today is the best restaurant in the world. <img
src = "http://static.se2.naver.com/static/full/20130612/emoticon/3_10.gif"> ^
M
I'll try to have a late lunch after eating delicious ~
<img src = "http://postfiles7.naver.net/20140206_134/aerichan_1391628394142NTC
rG_JPEG / IMG_9246.jpg? type = w1 ">
This is the second visit this time!

The image parsing module 120 sets the value 1 to inform the image flag IMAGE_FLAG of the mapping database 200 of the image URL extraction.

The DB management module 130 implements an interface with the mapping database 200 and stores the web data filtered and extracted by the collection module 110 in the mapping database 200.

The procedure 140 is executed after confirming the Web data collection end code, and may be referred to as a creation date extraction procedure (GET_DAUM_WRITE_DATE).

The procedure 140 performs a post-processing operation for extracting the creation date. There are HTML pages of the date information and title body information due to the iframe structure. It can not be extracted at the same time when collecting once, and post-treatment is necessary.

That is, the procedure 140 links the two pieces of information by linking, for example, a web site (blog) ID (03MpP) and a post ID (http://blog.daum.net/eastern/12704400). At this time, knowing the website (blog) ID and the post ID, you can get a record with the actual title and body (http://blog.daum.net/_blog/hdn/ArticleContentsView.do?blogid=03MpP&articleno=12704400&looping=0). have.

The integration agent 150 executes the image parsing module 120.

Referring to FIG. 4, the operation of the collecting unit 100 is such that the collecting module 110 generates a collecting field SCD (S201). The end of the collection is confirmed through the DB status code (S203).

The integration agent 150 instructs execution of image parsing (S205).

Then, the image parsing module 120 extracts the image URL in the SCD and updates it in the mapping database 200 (S207). Then, an image URL is displayed in the web data body and the image position (S209).

5, the collecting module 110 extracts the website ID and the post ID from the collecting module 110 (S301). After confirming the collection end code, the integration agent 150 executes the procedure 140 (S303).

Then, the procedure 140 extracts a creation date by linking the Web site ID and the post ID extracted in step S301 (S305). Then, the creation date extracted in step S305 is updated to the mapping database 200 (S307).

FIG. 6 is a block diagram showing the detailed configuration of the determination unit of FIG. 1, and FIG. 7 is a flowchart illustrating an operation of the determination unit of FIG.

Referring to FIG. 6, the determination unit 300 includes a DB management module 310 and a determination module 330.

The DB management module 310 implements an interface with the mapping database 200 and registers the values set by the determination module 330 in the mapping database 200.

The determination module 330 determines whether the web data collected by the collection unit is included in a predefined category. And sets the category flag of the mapping database to the inclusion value (1) if it is included in the predefined category, or to the inclusion value (-1) if it is not included in the predefined category.

Referring to FIG. 7, the operation of the determination unit 300 is such that the determination module 330 reads the web data body in record units (S401). Then, the determination module 330 loads the learning file (S403). Here, the learning file means a machine learning file. Then, the category is determined on a web site basis (S405). At this time, since it is time-consuming to extract interest information (POI) for the entire general web site, it is determined whether or not the category is included in order to reduce the object to be checked. At this time, a learning classification algorithm can be used.

As a result of the determination in step S405, the determination module 330 sets the category flag to 1 if the web data is included in the predefined category, and sets the category flag to -1 if the web data is not included in the category.

FIG. 8 is a block diagram showing the detailed configuration of the extracting unit of FIG. 1, and FIG. 9 is a flowchart showing the operation of the extracting unit of FIG.

8, the extraction unit 400 includes a DB management module 410, a preprocessing module 420, and an extraction module 430. [

The DB management module 410 implements an interface with the mapping database 200 and stores interest information (POI) extracted by the extraction module 430 in the mapping database 200.

The preprocessing module 420 arranges the texts included in the main text of the web data stored in the mapping database 200 on a line-by-line basis, and preprocesses the arranged texts to list only nouns other than auxiliary verbs or surveys.

The extraction module 430 performs tagging on the address and the telephone number in the preprocessed text. After the tagging process, a value for notifying interest information (POI) extraction is set in the interest information (POI) flag, and registered in the mapping database through the DB management module 410.

Referring to FIG. 9, the preprocessing module 420 reads the body of the web data in record units (S501).

The preprocessing module 420 loads the pattern in the regular expression setting file (S503). Here, the regular expression setting file is a structure for unifying and unifying patterns when addresses and telephone numbers have different forms. For example, if a telephone number of 000.0000.000 is found, conversion to a frequently used pattern, 000-0000-0000, increases the probability of being tagged with a telephone number. In other words, this is the regular expression configuration file that allows certain patterns to be found in the text.

The preprocessing module 420 performs regular expression processing according to the pattern of the loaded regular expression setting file (S505). In other words, regular expression processing refers to conversion of price information, business hours, and telephone number format in a blog body, which is not constant in format, to a certain format by using regular expressions in order to increase accuracy when extracting interest information (POI) through learning .

For example, in the case of price, it can be converted from 30,000 won to 30,000 won to 50,000 won, from 25,000 won to 25,000 won. In case of business hours, it can be converted from 3:00 am to 10:30 pm -> 3:00 am to 10:30 pm. In case of telephone number, it can be converted into 02) 526-5114 -> 02-526-5114, 02 526 5114 -> 02-526-5114.

The preprocessing module 420 performs token separation in English, Korean, and special units (S507). In order to improve the accuracy of extraction of interest information (POI) through segregation of learning, there is Pyrrhon to preprocess the contents of the text. Separate tokens in English, Korean, and special symbols.

Next, the extraction module 430 tags the address in the web data body and the telephone number (S509). Table 2 shows the results.

Address: <B-Add> ... . </ B-Add>
Phone number: <B-Tel> ... . </ B-Tel>

FIG. 10 is a block diagram showing the detailed configuration of the mapping unit of FIG. 1, and FIG. 11 is a flowchart showing the operation of the mapping unit of FIG.

Referring to FIG. 10, the mapping unit 500 includes a DB management module 510, a mapping module 520, and an address code conversion module 530.

The DB management module 510 implements an interface with the mapping database 200 and stores interest information (POI) extracted by the extraction module 430 in the mapping database 200.

The mapping module 520 searches the interest information (POI) index database 600 using the converted telephone number and address as keywords, obtains the ID of interest information (POI) corresponding to the converted telephone number and address, One ID is mapped to the extracted web data and stored in the mapping database 2000.

In addition, the mapping module 520 sets a value indicating the acquisition of the ID to the interest information (POI) flag when acquiring the ID of the POI corresponding to the converted telephone number and address.

The address code conversion module 530 converts the tagged telephone number into the POI data format and converts the address into the PNU code format.

Referring to FIG. 11, the operation of the mapping unit 500 accesses the mapping database 200 through the DB management module 510 (S601).

(POI), i.e., an address and a telephone number, from the mapping database 200 (S603).

The address code conversion module 530 converts the telephone number loaded in step S603 (S605). At this time, the telephone number is converted into the POI data format. For example, the telephone number '042 - 535 - 9915' can be converted into '004205359915' (padding each field to 4 digits).

The address code conversion module 530 converts the address into a PNU code (S607).

The mapping module 520 retrieves the POI ID from the interest information (POI) index DB 600 based on the PNU code converted in step S607 (S609). The information (telephone number, address) extracted at the time of searching can be selectively used for searching. It can be searched when there is only a telephone number, when there is only an address code, when there is only one information, and when both information exists. The mapping module 520 maps the retrieved POI ID to the corresponding blog.

12 is a block diagram showing the detailed configuration of the mapping management unit of FIG.

12, the mapping management unit 700 provides an interface through which the user can manage the mapping web data details, and includes a POI mapping management module 710 and a search module 730 in detail .

The POI mapping management module 710 performs mapping blog use registration processing, mapping blog unused processing, and mapping blog reuse processing. It is a function that manages whether or not the blog history that is automatically mapped from collection to POI mapping is finally used.

The search module 730 retrieves the POI mapping table and manages process flags. At this time, in the case of the process flag, it is for status management, and when it is displayed on the final management screen, the flag value is initialized to 0 as an unregistered state. It is determined that the mapping is normal and the flag value is updated to 1 at the time of registration by the administrator. It is judged that the mapping is wrong and the flag value at the time of registration is updated to -1 when the manager is unused.

FIG. 13 is a schematic diagram of an apparatus for generating interest information based on web collection according to another embodiment of the present invention. The apparatus includes a collecting unit 100 of the interest information generating apparatus based on the web collection described with reference to FIG. 1, A device that can be used to perform at least a part of the functions of the mapping unit 200, the determination unit 300, the extraction unit 400, the mapping unit 500, the interest information (POI) database 600, and the mapping management unit 700 .

13, the interest information generation apparatus 800 includes a processor 801, a memory 803, at least one storage device 805, an input / output (I / O) interface 807, (809).

The processor 801 may be implemented as a central processing unit (CPU) or other chipset, a microprocessor, and the like, and the memory 803 may be a dynamic random access memory (DRAM), a Rambus DRAM (RDRAM) SDRAM), static RAM (SRAM), and the like.

The storage device 805 may be a hard disk, a compact disk read only memory (CD-ROM), a compact disk rewritable (CD-RW), a digital video disk ROM, , An optical disk such as a blue-ray disk, a flash memory, various types of RAM, or a permanent or volatile storage device.

The I / O interface 807 also allows the processor 801 and / or the memory 803 to access the storage device 805 and the network interface 809 may be coupled to the processor 501 and / ) To access the network (not shown).

In this case, the processor 801 receives a program command for implementing at least some functions of the functions of the collecting unit 100, the determining unit 300, the extracting unit 400, the mapping unit 500, and the mapping management unit 700 It may be loaded into the memory 803 and controlled to perform the operations described with reference to FIG.

The memory 803 or the storage 805 may be connected to the processor 801 and may be connected to the collecting unit 100, the determining unit 300, the extracting unit 400, the mapping unit 500, Function can be performed.

The processor 801, the memory 803, the storage device 805, the I / O interface 807, and the network interface 809 shown in Fig. 13 may be embodied in one computer or distributed in a plurality of computers .

The embodiments of the present invention described above are not implemented only by the apparatus and method, but may be implemented through a program for realizing the function corresponding to the configuration of the embodiment of the present invention or a recording medium on which the program is recorded.

While the present invention has been particularly shown and described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, .

Claims (18)

A POI index DB storing index information of interest information (POI) classified by ID,
A collection unit for collecting each piece of web data from a plurality of web sites,
An extracting unit for extracting interest information (POI) from the web data collected by the collecting unit,
A mapping unit for mapping the web data including the extracted interest information to the acquired ID if the ID mapped to the interest information (POI) extracted by the extracting unit is obtained from the POI index database, and
And a mapping database for storing a mapping relation between the web data and the acquired ID,
The web data mapped to the ID of the POI is searched together with the POI,
The extracting unit extracts,
A preprocessing module for arranging texts included in the body of the web data periodically collected from a plurality of different web sites of different from each other in a line unit and performing a preprocessing for arranging only nouns except for auxiliary words or surveys on the arranged texts , And
And an extraction module for tagging the address and the telephone number in the preprocessed text,
Wherein the mapping unit comprises:
And acquiring an ID mapped to the address and the telephone number, and mapping the extracted web data to the ID and the extracted ID. The method according to claim 1,
Wherein,
(POI) generation device based on web collection that collects each piece of web data including articles registered on a website according to a user's interest from a plurality of web sites. 3. The method of claim 2,
Wherein,
A collection module for filtering and extracting web data corresponding to title, body, Uniform Resource Locator, collection date, creation date, and guidance from the collected web data, and
A DB management module for storing the web data filtered and extracted by the collection module in the mapping database,
(POI) generation device based on web collection. The method of claim 3,
Wherein the acquisition module comprises:
(POI) generation device based on web collection for collecting, filtering, and extracting the web data according to a web collection setting function preset by a user including a collection target URL, a collection link pattern setting, and a collection field pattern. 5. The method of claim 4,
Wherein,
An image parsing module for extracting an image tag URL and storing the image tag URL in the mapping database through the DB management module when the image tag is included in the collected web data,
(POI) generation device based on web collection. 6. The method of claim 5,
The image parsing module comprising:
(POI) generation device based on web collection that sets a value to inform the image flag of the mapping database of image URL extraction. The method according to claim 6,
Further comprising a determination unit for determining whether the web data collected by the collection unit is included in a predefined category,
The extracting unit extracts,
(POI) based on web collection to extract the POI from web data included in the predefined category. 8. The method of claim 7,
Wherein,
And setting the category flag of the mapping database as an included value if the category is included in the predefined category and setting the category flag of the mapping database as a preliminary value if the category flag is not included in the predefined category. delete 9. The method of claim 8,
Wherein the extraction module comprises:
Wherein the POI flag is set to a value indicating the extraction of the POI after the tagging process. 11. The method of claim 10,
Wherein the mapping unit comprises:
An address code conversion module for converting the tagged phone number into a POI data format and converting the address into a PNU code format,
Searches the POI index DB using the converted telephone number and address as keywords, obtains the ID of interest information (POI) corresponding to the converted telephone number and address, and transmits the obtained ID to the converted telephone number A mapping module for mapping the number and the address to the extracted web data and storing the mapping data in the mapping database
(POI) generation device based on web collection. 12. The method of claim 11,
Wherein the mapping module comprises:
Wherein the POI flag is set to a value indicating the acquisition of the ID to the POI flag when acquiring the ID of the POI corresponding to the converted phone number and address. 13. The method of claim 12,
A mapping management unit for providing an interface through which the user can manage the mapping web data history
(POI) generation device based on web collection. A method of generating a POI based on web collection, the method comprising:
Wherein the POI generation device collects web data from a plurality of web sites,
Obtaining an ID mapped to interest information (POI) extracted from the web data from a POI index database;
Mapping the web data including the extracted interest information to the acquired ID, and
And searching for the web data mapped to the ID of the POI when retrieving POI according to a user request,
Wherein the collecting comprises:
Extracting the POI including an address and a telephone number from a body of web data periodically collected from a plurality of different web sites,
The step of extracting the POI (POI)
Arranging the texts included in the main text in line units, and performing pre-processing for arranging only the nouns excluding the auxiliary verbs or the search for the arranged texts, and
Tagging the address and telephone number of the preprocessed text,
Wherein the mapping comprises:
And generating a POI based on web collection for mapping the mapped ID and the web data from which the POI is extracted. 15. The method of claim 14,
Wherein the collecting comprises:
Filtering and extracting web data corresponding to a title, a body, a Uniform Resource Locator, a collection date, a creation date, and a map from the collected web data,
Determining whether the web data is included in a predefined category, and
Extracting the interest information (POI) including the address and the telephone number from the body text of the web data extracted by the filtering, if it is included in the predefined category
(POI) based on web aggregation. 16. The method of claim 15,
Wherein the collecting comprises:
If the collected web data includes an image tag, extracting the image tag URL and displaying the extracted image tag URL at the image location and the body text
(POI) based on web aggregation. delete 17. The method of claim 16,
Wherein the mapping comprises:
Converting the tagged phone number into a POI data format,
Converting the address into a PNU code format,
Searching the POI index DB using the converted telephone number and address as keywords, and obtaining an ID of interest information (POI) corresponding to the converted telephone number and address, and
Mapping the acquired ID to the converted web number and the extracted telephone number and address
(POI) based on web aggregation.

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