JP2010086210A - Retrieval method, program, and server for preferentially displaying page corresponding to amount of information - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a retrieval method, a program, and a server for preferentially outputting not a page of a small amount of information but a page of a large amount of information in retrieving a Web page. <P>SOLUTION: A retrieval server 1 extracts a feature word included in a Web page to be retrieved through morphological analysis, and calculates a weight of the feature word by using TF-IDF. The retrieval server 1 is also provided with a relevant word DB 24 for specifying whether or not a plurality of feature words are relevant to each other, and decides whether or not the plurality of feature words included in the Web page are relevant to each other by using the relevant word DB 24. Then, the retrieval server 1 calculates the total weight of the plurality of relevant feature words, and adjusts the retrieval result by using the total weight. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a search method, a program, and a server thereof that preferentially display a page with a large amount of information, not a page with a small amount of information related to a search keyword in a search for a Web page.

  In recent years, websites, blogs and other contents accessible via the Internet have become searchable by using various search services, and not only academically but also in the lives of ordinary citizens, Or in corporate activities, it is indispensable.

  Many of such search services employ a method of searching content on the Internet by inputting a search keyword. Therefore, various search services have been devised in order to efficiently search for content that is inferred from the search keyword and that matches the search purpose of the user. For example, content with a high so-called page rank is often displayed higher in the search results.

  This page rank includes not only more search keywords but also more links from other pages, that is, more links, and the number of times viewed by the user (clicks). Many have been decided to be higher.

For example, according to Patent Document 1, when searching and displaying Web pages that exist in large numbers on the Internet, the score (weight) of the page is calculated by referring to the number of linked domains. The page rank is decided.
JP 2007-114903 A

  As described above, by outputting the search results using various data indicating the characteristics of the Web page, the conventional search service has attempted to display the search results in the order according to the user's needs.

  By the way, in recent years, the number of blog sites has increased, and this blog site frequently updates web pages, but each time it is updated, the theme changes so that the information becomes diffuse and the amount of information on one theme There are many things with few. In recent years, celebrities have opened such blog sites, and there are very popular blog sites.

  In such a situation, if the ranking of search results is determined by reflecting the number of linked links, the number of clicks, etc., even a popular blog site with a small amount of information related to the search keyword will be displayed as a high-order search result. There was a problem of being.

  Such a problem will be specifically described with reference to FIGS. In FIG. 9 (1), only the sentence 200 relating to “Olympic” is displayed, and the content is also enriched. On the other hand, in FIG. 9B, in addition to the sentence 201 related to “Olympic”, a sentence 202 and a sentence 203 related to other themes are displayed, and the content of the sentence 201 is also thin. Web page 2 is an example of a popular blog site.

  FIG. 10A is a diagram illustrating an example of a Web page weight indicating a feature word weight that is an importance (appearance frequency) of a feature word in the Web pages 1 and 2, a click history, and the number of link data. is there. A feature word is a characteristic phrase extracted from a morphological analysis of text data in a Web page (for example, a word or auxiliary verb removed from a result extracted from a morphological analysis) The feature word weight is an index indicating the weight of the feature word in the Web page calculated using TF (Term Frequency) / IDF (Inverse Document Frequency) which is an index based on the appearance frequency of the phrase. FIG. 10B is a diagram illustrating the weight (score) of the Web page when the user inputs “Olympic” as a search keyword in such a case.

  According to FIG. 10 (1), in the Web page 1 with a rich content about “Olympic”, the weight of TF / IDF is “30” for the characteristic word “Olympic”, but the content about “Olympic” is thin. In Web page 2, it is “20”. However, since the Web page 2 is popular as a blog site, the click history, the number of link data, and the like are larger than those of the Web page 1. For this reason, as shown in FIG. 10B, the Web page 2 with less content about “Olympic” may have a higher weight than the Web page 1 with more content. In such a case, when the user inputs “Olympic” as a search keyword, the search result is displayed with priority on the Web page 2 with a lighter theme and less content rather than the Web page 1 with a rich content. The Rukoto.

  From the user's perspective, the search keyword is “Olympic” rather than the name of a celebrity who is in charge of the blog, and the above results do not meet the user's needs.

  Accordingly, an object of the present invention is to provide a search method, a program, and a server thereof that preferentially output a page with a large amount of information, not a page with a small amount of information in the search for a Web page.

  The inventor has found a mechanism for preferentially displaying a page with a large amount of information in the search result by using the feature word weight of the feature word related to the search keyword, and has completed the present invention. Specifically, the present invention provides the following.

(1) A computer connected to a terminal via a communication network
A web page analyzing step of analyzing a web page to be searched and extracting a plurality of feature words indicating features in the web page;
A feature word weight calculating step of calculating a feature word weight indicating an appearance frequency of the extracted feature word in the Web page for each of the plurality of feature words;
A search method including
A related word DB for storing relevance of a plurality of feature words is provided,
A related word determining step of determining whether or not each of the plurality of feature words extracted by the web page analyzing step is related using the related word DB;
A web page weight calculating step of calculating a sum of feature word weights of feature words determined to be related as a related word weight;
An indexing storage step of storing the calculated related word weight in the indexing DB in association with the link data of the Web page;
Search method including

  According to this configuration of the present invention, the related word weight, which is the sum of the feature words determined to be related, is stored in the indexing DB in association with the link data of the Web page. Thereby, the information amount regarding the specific theme in a web page can be discriminate | determined appropriately. Therefore, in a computer process such as a process for outputting a search result, the search result can be adjusted so that a page with a large amount of information is output preferentially instead of a page with a small amount of information.

(2) The computer is
Receiving the request data including the search keyword from the terminal;
A search step of searching for a web page including the search keyword based on the search keyword received in the receiving step;
A web page adjustment step of adjusting a search result using a related word weight related to the search keyword among the web pages searched in the search step;
A transmission step of transmitting content including link data of the searched web page to the terminal based on the adjustment result of the web page adjustment step;
(1) The search method according to (1).

  According to such a configuration of the present invention, when searching for a Web page using a search keyword, the user's terminal can preferentially output a Web page with a large amount of information about the search keyword, which is suitable for the user's needs. A search method can be provided.

(3) The computer is
An average weight calculating step for calculating an average value of feature word weights of all feature words in the Web page;
A comparison weight calculation step of calculating a ratio at which the related word weight calculated by the Web page weight calculation step deviates from the average value;
(2) The search method according to (2), wherein the Web page adjustment step adjusts the search result using the ratio calculated in the comparison weight calculation step.

  According to such a configuration of the present invention, when determining a Web page with a large amount of information, since the ratio of the related word weight deviating from the average value in the Web page is used, the Web page of the characteristic word corresponding to the search keyword It is possible to appropriately determine the importance level in the web page of two or more.

  (4) The computer includes an acquisition step of periodically visiting a Web server connected via a communication network to acquire the Web page to be searched. (1) The search method according to any one of (3).

  According to such a configuration of the present invention, since the target Web page is periodically acquired, it is possible to always search using data of a new Web page.

  (5) A search program for causing a computer to execute the steps of the method according to any one of (1) to (4).

(6) A search server connected to a terminal via a communication network,
Web page analysis means for analyzing a Web page to be searched and extracting a plurality of feature words indicating features in the Web page;
Feature word weight calculating means for calculating a feature word weight indicating the appearance frequency of the extracted feature word in the Web page for each of the plurality of feature words;
A related word DB for storing relevance of a plurality of feature words;
Related word determination means for determining whether or not each of the plurality of feature words extracted by the web page analysis means is related using the related word DB;
Web page weight calculating means for calculating the sum of feature word weights of feature words determined to be related as related word weights;
Indexing storage means for storing the calculated related word weight in the indexing DB in association with the link data of the Web page;
A search server comprising:

  According to the present invention, it is possible to preferentially output a page with a large amount of information rather than a page with a small amount of information when searching for a Web page.

  Hereinafter, the best mode for carrying out the present invention will be described with reference to the drawings. This is merely an example, and the technical scope of the present invention is not limited to this.

(Embodiment)
[Overall configuration of search system and functional configuration of search server]
FIG. 1 is a diagram showing the overall configuration of the search system 100 and the functional configuration of the search server 1 according to the present embodiment.

  The search system 100 includes a search server 1, a content server 2, a communication network 3, and a terminal 4. As shown in FIG. 1, a search server 1, a content server 2, and a terminal 4 are connected to be communicable with each other via a communication network 3 represented by a communication line such as the Internet.

  The search server 1 includes a control unit 10 and a storage unit 20. The control unit 10 includes a web page acquisition unit 11, a web page analysis unit 12, a feature word weight calculation unit 13, a related word determination unit 14, a web page weight calculation unit 15, a reception unit 16, and a search unit 17. And content transmission means 19. The storage unit 20 includes a collection Web page database (hereinafter, the database is also referred to as a DB) 22, a related term DB 24, and an indexing DB 26. The contents of each DB will be described later.

  The search server 1 is not limited in the number of hardware, and may be configured by one or a plurality of hardware as necessary. In the case of a plurality of hardware, each hardware may be connected via the communication network 3. For example, the functions of the present embodiment may be realized by using a separate server for each function described later and linking the servers by transmitting and receiving signals between the servers.

  The Web page acquisition unit 11 plays a role of a crawler that periodically circulates the content server 2 storing the Web page (content) and collects (acquires) a newly created Web page or an updated Web page. The collected web pages are stored in the collected web page DB 22 as needed.

  The web page analysis unit 12 extracts feature words from words extracted by morphological analysis of text data of web pages stored in the collection web page DB 22.

  The feature word weight calculation unit 13 calculates feature word weights indicating the importance (appearance frequency) of the extracted feature words in the Web page. Here, the feature word weight is calculated using TF (Term Frequency) / IDF (Inverse Document Frequency), which is an index based on the appearance frequency of the phrase.

  The related word determination unit 14 determines the presence / absence of a related word related to the calculated feature word for each Web page using the related word DB 24. In addition, a related word means the other characteristic word relevant to a certain characteristic word. Here, the administrator of the server can arbitrarily set whether or not each feature word is related, and can be changed as appropriate.

  The web page weight calculation unit 15 calculates the related word weight of the related word determined by the related word determination unit 14 (for example, the sum of the weights of a plurality of related characteristic words), and the related word weight and the characteristic word weight. Web page weight including the click history and the number of link data is calculated. Then, the web page weight calculation unit 15 stores the calculated web page weight in the indexing DB 26 (see FIG. 4 (2) described later).

  The receiving unit 16 receives request data including a search keyword from the terminal 4. The search means 17 searches for a Web page containing the search keyword. The web page adjusting unit 18 adjusts the search result using the web page weight calculated by the web page weight calculating unit and the search keyword. The content transmission unit 19 transmits the content including the link data of the web page to the terminal 4 based on the adjustment result of the web page adjustment unit 18.

  The content server 2 is a content DB server that stores a plurality of Web pages. As long as the content server 2 is connected to the communication network 3, it corresponds to a content DB server storing any web page in the world.

  The terminal 4 is an apparatus including an input unit such as a keyboard and a mouse for a user to input an operation for reproducing the content, and a display screen for displaying the content. Using the terminal 4, the user can input a search keyword or view content.

[Hardware configuration diagram of search server 1]
FIG. 2 is a diagram illustrating a hardware configuration of the search server 1 according to the present embodiment. The server in which the present invention is implemented may be a standard server, and an example of the configuration is shown below.

  The search server 1 includes a central processing unit (CPU) 1010 (a plurality of CPUs such as a CPU 1012 may be added in a multiprocessor configuration), a bus line 1005, a communication I / F (I / F: interface) constituting the control unit 10. ) 1040, a main memory 1050, a basic input output system (BIOS) 1060, a display device 1022, an I / O controller 1070, an input device 1100 such as a keyboard and a mouse, a hard disk 1074, an optical disk drive 1076, and a semiconductor memory 1078. The hard disk 1074, the optical disk drive 1076, and the semiconductor memory 1078 are collectively referred to as the storage unit 20.

  The control unit 10 is a part that controls the search server 1 in an integrated manner. By appropriately reading and executing various programs stored in the hard disk 1074, the control unit 10 cooperates with the hardware described above, and performs various functions according to the present invention. Is realized.

  The communication I / F 1040 is a network adapter when the search server 1 transmits / receives information to / from the terminal 4 (FIG. 1) via the communication network 3 (FIG. 1). The communication I / F 1040 may include a modem, a cable modem, and an Ethernet (registered trademark) adapter.

  The BIOS 1060 records a boot program executed by the CPU 1010 when the search server 1 is started up, a program depending on the hardware of the search server 1, and the like.

  The display device 1022 includes a display device such as a cathode ray tube display device (CRT) or a liquid crystal display device (LCD).

  The I / O controller 1070 can be connected to a storage unit 20 that is a storage device such as a hard disk 1074, an optical disk drive 1076, and a semiconductor memory 1078.

  The input device 1100 accepts input by the administrator of the search server 1.

  The hard disk 1074 stores various programs for causing the hardware to function as the search server 1, programs for executing the functions of the present invention, and DB tables and records to be described later. The search server 1 can also use an external hard disk (not shown) as an external storage device.

  As the optical disc drive 1076, for example, a DVD-ROM drive, a CD-ROM drive, a DVD-RAM drive, or a CD-RAM drive can be used. In this case, the optical disk 1077 corresponding to each drive is used. A program or data may be read from the optical disk 1077 by the optical disk drive 1076 and provided to the main memory 1050 or the hard disk 1074 via the I / O controller 1070.

  The computer referred to in the present invention refers to an information processing device including a storage device, a control unit, and the like. The search server 1 includes an information processing device including a storage unit 20, a control unit 10, and the like. The processing device is included in the concept of the computer of the present invention.

[Hardware Configuration of Content Server 2]
The content server 2 has the same configuration as the search server 1 described above. In addition to the content server 2, the search server 1 may have a content DB that stores Web pages in the same manner as the content server 2.

[Hardware configuration of terminal 4]
The terminal 4 has the same configuration as that of the search server 1 described above. For example, the storage unit 20 may be a drive in which an external memory can be inserted instead of the optical disc drive 1076. The display device 1022 may have the function of the input device 1100 as a touch panel. Furthermore, the terminal 4 may include a sensor such as an acceleration sensor, and the sensor may have the function of the input device 1100.

[Flowchart of main processing]
FIG. 3 is a flowchart of the indexing process of the search server 1 according to this embodiment. For example, the indexing process is periodically performed at a predetermined timing determined by the administrator of the search server 1.

  S1: The control unit 10 (Web page acquisition unit 11) acquires a Web page by crawling the content server 2. And the control part 10 memorize | stores the acquired web page in collection | recovery web page DB22.

  S2: The control unit 10 (Web page analysis means 12) performs Web page analysis processing. Specifically, the web page analysis unit 12 performs morphological analysis on the web page stored in the collected web page DB 22 and extracts a phrase from the text data of the web page. Then, a characteristic word in the Web page, that is, a characteristic word is extracted from the word / phrase.

  S3: The control unit 10 (feature word weight calculating means 13) calculates a feature word weight that is a weighting of the feature word in the Web page.

  S4: The control part 10 (related word determination means 14) determines the presence or absence of the related word regarding the calculated several characteristic word. In addition, related word DB24 (refer FIG. 4 (1)) is used for determination of the presence or absence of a related word.

  S5: The control unit 10 (Web page weight calculation means 15) calculates a Web page weight indicating the characteristics of the Web page, and stores the calculated Web page weight in the storage unit 20 (indexing DB 26). Here, the Web page weight includes a related word weight, a feature word weight, a click history, and the number of link data. The feature word weight is calculated by obtaining the weight in the Web page for each calculated feature word using TF / IDF. The related word weight is the sum of the weights of a plurality of feature words determined to be related. The click history is the number of times that the web page is displayed on the terminal 4 during a predetermined period, and the number of link data is the number of web pages to which the web page is linked.

[Related Word DB 24 and Indexing DB 26]
FIG. 4 is a diagram showing the related term DB 24 and the indexing DB 26 stored in the storage unit 20 according to the present embodiment. The related word DB 24 is a DB used when the control unit 10 determines whether or not the feature word in the Web page is related in S4 of FIG. 3 described above. Note that the presence or absence of relevance can be arbitrarily set in advance by the administrator of the search server 1. The indexing DB 26 is a database in which the control unit 10 stores Web page weights including related word weights in S5 of FIG. 3 described above.

  The related word DB 24 shown as an example in FIG. 4A stores the related words arbitrarily set by the administrator for each related word ID. For example, referring to “Related Word ID 010”, “Olympic”, “Beijing”, “London”, “Tokyo” and the like are stored as related feature words in “Olympic”.

  The indexing DB 26 shown as an example in FIG. 4B has a URL (Uniform Resource Locator) indicating the position information of the Web page with the Web page ID as key information, and corresponding feature word weight, related word weight, and click history. , And a web page weight including link number data. In FIG. 4B, information about Web page 1 (FIG. 8 (1)) and Web page 2 (FIG. 8 (2)) is shown as an example.

  The related word weight stores the sum of the weights of a plurality of feature words determined to be related for each related word ID. For example, in “Web page ID001”, “Olympic (weight: 30)”, “Beijing (weight: 25)”, “Olympic (weight: 15)”, etc. are calculated as characteristic words. “Related word ID 010” is set to be all related. Therefore, the related word weight of the “related word ID 010” is the sum of the weights of these feature words and becomes “70” (= 30 + 25 + 15). Similarly, in “Web page ID 002”, “Olympic (weight: 20)”, “Midtown (weight: 15)”, “Sea (weight: 10)”, etc. are calculated as characteristic words. "" Is determined that only "Olympic" is relevant. Therefore, the related word weight of “related word ID 010” is “20”.

  In the present embodiment, the click history and the number of link data are stored as the Web page weight, but may be replaced with another index indicating the characteristics related to the Web page.

[Search process flowchart]
Next, a search process using the related word weights described above will be described. FIG. 5 is a flowchart of search processing in the search server 1 according to the present embodiment.

  S <b> 21: The control unit 10 (reception unit 16) receives request data including a search keyword from the terminal 4.

  S22: The control unit 10 (search means 17) searches for a Web page including the keyword based on the received search keyword. For the search of this Web page, a Web page stored in the collection Web page DB 22 can be used.

  S23: The control unit 10 (Web page adjustment means 18) adjusts the order in which the link data is arranged from the search result using the indexing DB 26. In this adjustment, first, the related word weight of the related word ID corresponding to the search keyword is extracted from the Web page targeted as the search result. Next, the extracted related word weights are corrected by an index indicating characteristics relating to the Web page such as a click history and the number of link data, and a total weight is calculated. Then, the Web pages targeted as search results are output in order from the one with the largest calculated total weight.

  For example, “Web page ID 001” and “Web page ID 002” when the search keyword is “Olympic” will be described as an example. The related word ID corresponding to the search keyword “Olympic” is “010”, and the related word weight of “Web page ID001” is “70” as shown in FIG. In this case, when corrected based on the click history, link number data, etc., the total weight of “Web page ID001” is “90” as shown in FIG. Similarly, the related word weight of “Web page ID 002” is “20” as shown in FIG. 4B, and when this is corrected, the total weight of “Web page ID 002” is “55” as shown in FIG. Become.

  S24: The control unit 10 creates content in which the link data of the Web page is arranged based on the adjustment result. In this case, the URL value shown in FIG.

  S25: The control unit 10 (content transmission unit 19) transmits the created content to the terminal 4.

  As described above, in this embodiment, the total weight of a page with a large amount of information for one theme can be set higher than a page with a small amount of information, and as a result, a page with a large amount of information is displayed at the top of the search result. be able to. That is, even if a page with a small amount of information about one theme has been displayed in the top of the search results when the click history or the number of link data is large (see FIGS. 9 and 10), the Web page It is possible to preferentially display a page with a large amount of information by calculating related feature words as a summary related word weight.

  On the other hand, since it is possible to reflect the index indicating the characteristics of the Web page such as the click history and the number of link data in the search result, the more popular Web page is preferentially displayed with the same amount of information. Thus, the search results can be displayed in the order according to the user's needs.

[Preferred example of comparison of each Web page]
Here, since the feature word weight calculated using TF / IDF is a relative value in each Web page, it may not be suitable for comparison of Web pages. For example, Web page 3 (ID: 003) in FIG. 7A is a blog-type Web page, and an article dated August 1 includes a sentence 200 having exactly the same content as Web page 1. After August 2nd, another sentence 205 is described.

  In this case, when the feature word weight of the Web page 3 is calculated using TF / IDF, as shown in FIG. 7B, “Olympic (weight: 20)”, “Beijing (weight: 15)”, “Olympic” (Weight: 5) ”, and the related word weight of“ related word ID 010 ”is“ 40 ”. On the other hand, as shown in FIG. 4 (2), in the Web page 1 on which the sentence 200 having exactly the same content is described, “Olympic (weight: 30)”, “Beijing (weight: 25)”, “Olympic (weight: 15) ”, and the related word weight of“ related word ID 010 ”is“ 70 ”.

  That is, even if the exact same sentence is described in the web page, the feature word weight calculated using TF / IDF differs depending on other sentences in the web page. The word weight will vary greatly. In this case, when “Olympic” is input as a search keyword, it becomes a problem which of the Web page 1 and the Web page 3 is displayed at the top of the search result.

  In this embodiment, in this embodiment, the ratio (weight for comparison) that the related word weights deviate from the average value (average weight) of the feature word weights of all the feature words in the Web page is compared. Thus, each Web page may be compared. This ratio can be calculated by “(related word weight−average weight) / related word weight”.

  Specifically, in the Web page 1, the average value of the feature word weights of all the feature words in the Web page is “18”, and the comparison weight for the related word weight of the “related word ID 010” is “0.74” (= (70−18) / 70). Similarly, in the Web page 3, the average value in the Web page is “10”, and the saving weight is “0.75” (= (40−10) / 40).

  By calculating and comparing the comparison weights in this way, the Web page 1 and the Web page 3 can be set to substantially the same order of search results. That is, if the Web page has the same amount of information for one theme, the same search result rank can be obtained regardless of the remaining information in the Web page. As a result, in the present embodiment, the search results can be adjusted by the absolute index (the ratio deviating from the average value, that is, the importance in the Web page) in all Web pages, and more appropriate search Results can be provided to the user.

  Specifically, in S3 of FIG. 3, the control unit 10 (feature word weight calculating means 13) calculates the feature word weight in the web page and calculates the average value of the feature word weight in the web page. This can be realized by calculating the related word weight and the comparison weight in S5 of FIG. 3 by the control unit 10 (Web page weight calculating means 15).

(Deformation)
[Modification of Related Word DB]
In the above embodiment, the feature words determined to be related are simply added. However, as shown in FIG. 8, the adding ratio may be varied depending on the degree of relatedness. For example, “Beijing” and “Tokyo” are considered to be related to “Olympic Games” with “Related Word ID 010”, but “Beijing”, where the date was held, is close to “Tokyo”. The relevance may be higher than that. Note that the degree of these relations can be arbitrarily set by the administrator of the search server 1 and can be changed as appropriate.

[Calculation of feature word weights]
In the above embodiment, the related word weight is calculated in the indexing process periodically performed at a predetermined timing (S5). However, the present invention is not limited to this. For example, the related word weight may be calculated after receiving the search keyword input by the user in the search process. With such a configuration, it is sufficient to calculate the related word weight only for the related word ID corresponding to the search keyword.

It is a figure which shows the whole structure of a search system, and the function structure of a search server. It is a figure which shows the hardware constitutions of a search server. It is a flowchart of the indexing process of a search server. It is a figure which shows the related term DB and indexing DB which are stored in a memory | storage part. It is a flowchart of the search process in a search server. It is a figure which shows an example of the search result in a search server. It is a figure which shows the suitable example about contrast of each web page. It is a figure which shows another embodiment of related word DB. 2 is a diagram illustrating an example of a web page 1 and a web page 2. FIG. It is a figure which shows the example of calculation of the total weight of a web page.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Search server 2 Content server 4 Terminal 10 Control part 11 Web page acquisition means 12 Web page analysis means 13 Feature word weight calculation means 14 Related word determination means 15 Web page weight calculation means 16 Reception means 17 Search means 18 Web page adjustment means 19 Content transmission means 20 Storage unit 22 Collection Web page DB
24 related terms DB
26 Indexing DB
100 search system

Claims (6)

A computer connected to the terminal via a communication network
A web page analyzing step of analyzing a web page to be searched and extracting a plurality of feature words indicating features in the web page;
A feature word weight calculating step of calculating a feature word weight indicating an appearance frequency of the extracted feature word in the Web page for each of the plurality of feature words;
A search method including
A related word DB for storing relevance of a plurality of feature words is provided,
A related word determining step of determining whether or not each of the plurality of feature words extracted by the web page analyzing step is related using the related word DB;
A web page weight calculating step of calculating a sum of feature word weights of feature words determined to be related as a related word weight;
An indexing storage step of storing the calculated related word weight in the indexing DB in association with the link data of the Web page;
Search method including The computer is
Receiving the request data including the search keyword from the terminal;
A search step of searching for a web page including the search keyword based on the search keyword received in the receiving step;
A web page adjustment step of adjusting a search result using a related word weight related to the search keyword among the web pages searched in the search step;
A transmission step of transmitting content including link data of the searched web page to the terminal based on the adjustment result of the web page adjustment step;
The search method according to claim 1, further comprising: The computer is
An average weight calculating step for calculating an average value of feature word weights of all feature words in the Web page;
A comparison weight calculation step of calculating a ratio at which the related word weight calculated by the Web page weight calculation step deviates from the average value;
The search method according to claim 2, wherein the Web page adjustment step adjusts a search result using the ratio calculated in the comparison weight calculation step. The computer includes an acquisition step of periodically visiting a Web server connected via a communication network to acquire the Web page to be searched;
The search method according to any one of claims 1 to 3, wherein:   The search program for making a computer perform the step of the method of any one of Claims 1-4. A search server connected to a terminal via a communication network,
Web page analysis means for analyzing a Web page to be searched and extracting a plurality of feature words indicating features in the Web page;
Feature word weight calculating means for calculating a feature word weight indicating the appearance frequency of the extracted feature word in the Web page for each of the plurality of feature words;
A related word DB for storing relevance of a plurality of feature words;
Related word determination means for determining whether or not each of the plurality of feature words extracted by the web page analysis means is related using the related word DB;
Web page weight calculating means for calculating the sum of feature word weights of feature words determined to be related as related word weights;
Indexing storage means for storing the calculated related word weight in the indexing DB in association with the link data of the Web page;
A search server comprising:

Images