JP2008226204A - Device, method, and program for gathering web information - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To reconstruct semi-structured or unstructured web information such as an HTML file and a PDF file for integrating necessary web information and facilitating classification and search. <P>SOLUTION: An attribute and an attribute value of gathered meta-information are compared with a vocabulary set list to determine whether they correspond or not. Then, a web information integration device refers to an attribute characteristic rule to determine whether they correspond or not. The web information integration device assumes the meta-information coincident in the all of determinations as information related to a product and stores the meta-information and the web information. The web information integration device also stores integration information coincident with the vocabulary set list and a rule coincident with the attribute characteristic rule as meta-metainformation. The meta-metainformation is used by a retrieval means for searching optional meaning from the stored web information. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a web information collection apparatus, a web information collection method, and a web information collection program, and more particularly to a web information collection apparatus, a web information collection method, and a web information collection program that support industry structure analysis.

  When a company develops a new product, an analysis (for example, SWOT analysis) for grasping the trends of other competing companies and drafting a corporate strategy may be executed. This trend can be grasped by collecting function lists (function lists) held by competitors' products (other companies' products) and grasping trends in data related to other companies' products over time. It is necessary to recognize.

  In addition, when a company develops a new product, not only the trends of competitors, but also the changes in the parts prices of parts suppliers in the company, the price negotiation ability of companies and general consumers who sell to them, etc. It is necessary.

  In recent years, with the spread of the Internet, companies and individuals have increased the number of information disclosed on websites. Increasingly, information published on Web sites (hereinafter referred to as Web information) is collected, and SWOT analysis based on the Web information is performed.

  In order to execute a useful analysis for marketing strategy and corporate strategy planning, it is required to appropriately classify and organize collected Web information. It is often difficult for humans to organize Web information by looking at the contents. When Web information to which meta information (for example, RDF (Resource Description Framework)) indicating information attributes is added is published, the information processing apparatus collects the Web information and uses the meta information. Information may be classified and organized. As an example, RSS (Rich Site Summary) is rapidly spreading as a summary of the latest information on websites of companies and the like. Techniques relating to such information classification and organization are known (see, for example, Patent Documents 1 to 9).

  For example, Patent Document 1 (Japanese Patent Application Laid-Open No. 2004-302694) discloses a technique for selecting information using a necessary technical information DB or a needs information DB in which information on competitors is defined in advance. Japanese Patent Laid-Open No. 2005-165736 discloses a technique for collecting information corresponding to product functions and their images. Patent Document 3 (Japanese Patent Application Laid-Open No. 2005-222489) discloses a technique for acquiring data indicating a competitive relationship between product types. Patent Document 4 (Japanese Patent Application Laid-Open No. 2003-248737) describes meta information associated with Web information. Patent Document 5 (Japanese Patent Application Laid-Open No. 2004-133652) discloses a technology related to a management solution system that analyzes management information and presents strategy information. Patent Document 6 (Japanese Patent Application Laid-Open No. 2004-228780) describes the meta-metadata. Patent Document 7 (Japanese Patent Laid-Open No. 2006-134183) describes a technique for aggregating words that can be taken to have the same meaning based on a topic word aggregation rule. Patent Document 8 (Japanese Patent Application Laid-Open No. 07-31616) describes a technique for setting an attribute characteristic rule and selecting an attribute. Patent Document 9 (Japanese Patent Application Laid-Open No. 08-030626) describes a hiragana notation fluctuation in a Japanese reading search dictionary.

JP 2004-302694 A Japanese Patent Laying-Open No. 2005-165736 Japanese Patent Laid-Open No. 2005-222489 JP 2003-248737 A Japanese Patent Laid-Open No. 2004-133651 JP 2004-228780 A JP 2006-134183 A Japanese Patent Laid-Open No. 07-311616 Japanese Patent Laid-Open No. 08-030626

  In the prior art, in order to determine whether the Web information is related information, the contents (text) are matched with lexical analysis, syntax analysis, and dictionary data holding product specific information. For this reason, it is difficult to accurately interpret how to express the contents of Web information, fluctuations, typographical errors, and the like, and information directly related to a certain target may not be acquired.

  In addition, when the data generation time is not included in the information on the Web, it is difficult to determine information related to past or future products that are out of the target life cycle. In addition, when information on the Web does not have rules for determining background knowledge of the industry such as services related to an object, it may be difficult to determine information related to the object. As a result, Web information that is not related in terms of target marketing management may be collected. In addition, there are cases where related Web information cannot be collected.

  In addition, when there is no rule necessary for the semantic search of the collected Web information, it is difficult to perform a search more than a full text search using keywords. As a result, it may be difficult to search for fragmented information from the collected Web information. For example, to extract information on all products and services that use a certain product, or to extract information on R & D, sales, etc. related only to a certain product, etc. May be difficult.

  The means for solving the problem will be described below using the numbers used in [Best Mode for Carrying Out the Invention]. These numbers are added to clarify the correspondence between the description of [Claims] and [Best Mode for Carrying Out the Invention]. However, these numbers should not be used to interpret the technical scope of the invention described in [Claims].

  In order to solve the above problems, a vocabulary set list storage unit (4) that holds a vocabulary set list, an attribute characteristic rule storage unit (5) that holds attribute characteristic rules, Web information, and meta data associated with the Web information An information collecting unit (2) that collects information, and an information determining unit (3) that determines whether the Web information is information related to a target based on the collected meta-information An information aggregating apparatus (1) is configured. Here, the information determination unit (3) collates the attribute of the Web information specified based on the meta information with the vocabulary set list. In addition, when the vocabulary set matching the attribute is included in the vocabulary set list, the attribute and the attribute characteristic rule are collated. When the attribute matches the attribute characteristic rule, it is determined that the Web information corresponding to the meta information is information related to the target.

  In the Web information aggregating apparatus (1), an RSS (Rich Site Summary) information collecting unit (14) that collects RSS data from a Web site that publishes Web information, and individual Web information from the RSS data. The structure provided with the RSS information analysis part (15) which extracts meta information of this may be sufficient. In this case, the RSS information collection unit (14) accesses the website and supplies the RSS data collected from the website to the RSS information analysis unit (15). The RSS information analysis unit (15) supplies the information collection unit (2) with the meta information obtained by decomposing the RSS data into individual Web information and meta information. And it is preferable to have the structure which supplies the said Web information obtained by the decomposition | disassembly to an information determination part (3). Here, the information determination unit (3) collects Web information based on link information to the text shown in the meta information supplied from the RSS information analysis unit (15). ).

In the Web information aggregation device (1), the vocabulary set list preferably includes a plurality of vocabulary sets. Further, each of the plurality of vocabulary sets is preferably a set of character strings indicating the attributes included in the meta information and having character strings having the same meaning and different notation as one category.
Further, in the Web information aggregating apparatus (1), the attribute characteristic rule preferably indicates a constraint condition between different attributes.

  The Web information aggregation device (1) may further include an information search unit (7). In this case, when the information determination unit (3) determines that the Web information is information related to the target, the information determination unit (3) may create link information to the Web information and meta information as meta-meta information. preferable. In response to the Web information search request, the information search unit (7) acquires the Web information based on the link information of the meta-meta information that matches the search request and supplies the Web information to the search request transmission source. It is preferable to have a configuration.

In order to solve the above problem, a computer comprising a vocabulary set list storage unit (4) for holding a vocabulary set list and an attribute characteristic rule storage unit (5) for holding attribute characteristic rules is provided as a Web information aggregating apparatus. A Web information aggregation program showing a procedure for functioning as (1) is configured. Here, the Web information aggregation program is
(A) collecting web information and meta information accompanying the web information;
And (b) determining whether the Web information is information related to a target based on the collected meta information, and the step (b) includes:
The attribute of the Web information specified based on the meta-information is compared with the vocabulary set list, and when the vocabulary set matching the attribute is included in the vocabulary set list, the attribute and the attribute characteristic rule are If the attribute matches the attribute characteristic rule, the computer is identified as a Web information aggregating apparatus (1) by a method including determining that the Web information corresponding to the meta information is information related to the object. ).

In the Web information aggregation program,
(C) collecting RSS (Rich Site Summary) data from a website that publishes web information;
(D) extracting meta information of individual Web information from the RSS data, and the step (c) includes:
Accessing the website and supplying RSS data collected from the website;
The step (d) includes:
Supplying the information collection unit (2) with the meta information obtained by decomposing the RSS data into individual Web information and meta information, and the Web information obtained by the decomposition as the information determination unit ( It may be a Web information aggregation program that causes a computer to function as the Web information aggregation device (1) by a method including the step of supplying to 3).

  In the Web information aggregation program, the vocabulary set list includes a plurality of vocabulary sets, and each of the plurality of vocabulary sets is a character string indicating the attribute included in the meta information, has the same meaning, and has a notation method. It is preferable that the web information aggregation program causes the computer to function as the web information aggregation device (1) when the character strings are aggregates of different character strings as one category.

  In the Web information aggregation program, the attribute information rule is preferably a Web information aggregation program that causes the computer to function as the Web information aggregation device (1) when the attribute characteristic rule indicates a constraint condition between different attributes.

In the Web information aggregation program,
(E) In response to a search request for Web information, the method includes the step of acquiring the Web information and supplying the Web information to a transmission source of the search request.
When it is determined that the Web information is information related to the object, a step of creating link information to the Web information and meta information as meta-meta information,
The step (e) includes:
In response to the search request for the Web information, a Web information aggregating apparatus (1) is obtained by a method of acquiring the Web information based on link information of meta-meta information matching the search request and supplying the Web information to a search request transmission source. It is preferable that the program is a Web information aggregation program that functions as

Moreover, in order to solve the said subject, Web information is gathered by the following chain of actions. Here, the Web information aggregation method is
(A) collecting web information and meta information accompanying the web information;
(B) determining whether the Web information is information related to a target based on the collected meta-information,
The step (b)
Collating the attribute of the Web information specified based on the meta information with the vocabulary set list read from the vocabulary set list storage unit (4);
Collating the attribute with the attribute characteristic rule read from the attribute characteristic rule storage unit (5) when the vocabulary set matching the attribute is included in the vocabulary set list;
Preferably, when the attribute matches the attribute characteristic rule, the Web information aggregation method includes a step of determining that the Web information corresponding to the meta information is information related to the target.

In the Web information aggregation method,
(C) collecting RSS (Rich Site Summary) data from a website that publishes web information;
(D) extracting meta information of individual Web information from the RSS data, and the step (c) includes:
Accessing the website and supplying RSS data collected from the website;
The step (d) includes:
Supplying the information collection unit (2) with the meta information obtained by decomposing the RSS data into individual Web information and meta information;
It may be a Web information aggregation method including a step of supplying the Web information obtained by the decomposition to the information determination unit (3).

In the Web information aggregation method, the vocabulary set list includes a plurality of vocabulary sets, and each of the plurality of vocabulary sets is a character string indicating the attribute included in meta information, has the same meaning, and has a notation method. It is preferable that it is a set in which character strings having different values are aggregated as one category.
In the Web information aggregation method, it is preferable that the attribute characteristic rule indicates a constraint condition between different attributes.

In the Web information aggregation method,
(E) In response to a search request for Web information, a step of acquiring the Web information and supplying it to a transmission source of the search request may be provided. In this case,
The step (b)
When it is determined that the Web information is information related to the object, a step of creating link information to the Web information and meta information as meta-meta information,
The step (e) includes:
In response to a search request for the Web information, it is preferable that the Web information is acquired and supplied to a transmission source of the search request based on link information of meta-meta information that matches the search request.

  The above-mentioned attribute characteristic rule preferably indicates a constraint condition between attributes and can define a function rule, a symmetry rule, a transition rule, and the like. Here, it is preferable that the function rule uniquely determines the relationship between attributes and determines the existence condition of the dependent attribute. It is preferable that the symmetry rule indicates a condition in which the function rule is mutually established between attributes. It is preferable that the transition rule indicates a transition condition such that the attribute A → the attribute C is established if the attribute A → the attribute B and the attribute B → the attribute C among the three or more attributes. Moreover, it is preferable that the meta information includes a classification, an outline, a generation time, and the like of the content of the Web information.

  The Web information aggregating apparatus collates the attributes and attribute values of the collected meta information with the vocabulary set list and determines whether or not they match. Subsequently, the Web information aggregating apparatus collates with the attribute characteristic rule and determines whether or not they match. The Web information aggregating apparatus regards meta information matched in all the determinations as information related to the product, and stores the meta information and Web information. Also, the aggregate information matched in the vocabulary set list and the rule matched in the attribute characteristic rule are stored as meta-meta information. In order to perform an arbitrary semantic search from the stored Web information, this meta-meta information is used as a search means.

  In some cases, the notation of attributes and attribute values (phrases) included in the meta information is not uniform. Therefore, the phrase classification may be performed using an ontology dictionary in which the meanings of the phrases are integrated.

  According to the present invention, when analyzing an industry structure as an external environment analysis, necessary Web information is obtained by restructuring Web information in a semi-structured / unstructured state such as an HTML file or a PDF file. It is possible to aggregate and facilitate classification and search.

[First Embodiment]
Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. FIG. 1 is a block diagram illustrating a configuration of a Web information aggregation device 1 according to the first embodiment of the present invention. The Web information aggregating apparatus 1 according to the present embodiment is a meta information indicating attributes (themes, creation times, etc.) of Web information in order to acquire information related to the life cycle of a certain product from Web information published on the Internet. Information is used to determine Web information collection. Referring to FIG. 1, a Web information aggregating apparatus 1 includes an information collection unit 2, an information determination unit 3, a vocabulary set list storage unit 4, an attribute characteristic rule storage unit 5, an information storage unit 6, and an information search unit. 7. The information storage unit 6 includes a Web information storage unit 11 that stores Web information, a meta information storage unit 12 that stores meta information, and a meta meta information storage unit 13 that stores meta meta information. .

  The vocabulary set list storage unit 4 holds data indicating a list having a plurality of vocabulary sets (vocabulary set list). In the vocabulary set list, attributes and attribute values considered in the same concept are configured as a vocabulary set. The attribute characteristic rule storage unit 5 holds data indicating attribute characteristic rules. The attribute characteristic rules include the product life cycle such as “development and sales” and the relationship with the indirectly related business such as “a product is used as a product for another product or another service business”. It is shown as an attribute characteristic rule.

  The information collecting unit 2 collects Web information such as an HTML file or a PDF file that is disclosed on the Internet, and meta information given to the Web information. The information determination unit 3 compares the attributes and attribute values of the collected meta information with the vocabulary set list of the vocabulary set list storage unit 4 and determines whether or not they match. The information determination unit 3 collates the attribute and attribute value of the collected meta information with the attribute characteristic rule of the attribute characteristic rule storage unit 5 and determines whether or not they match. When the information determination unit 3 matches the determination, the information determination unit 3 regards the meta information as information related to the product, and stores the meta information and the Web information in the information storage unit 6. Further, the information determination unit 3 stores the aggregate information matched in the vocabulary set list, the rule matched in the attribute characteristic rule, and the link information to the stored Web information and meta information in the information storage unit 6 as meta meta information. To do.

  In response to the Web information search request, the information search unit 7 replaces the search request with aggregated information and attribute characteristic rules. The information search unit 7 acquires all the meta information that matches the aggregate information, the attribute, and the attribute characteristic rule from the information storage unit 6, acquires Web information from the link information of each meta meta information, and returns it.

  The Web information aggregating apparatus 1 holds, for each Web information, information that matches the vocabulary set and the corresponding attribute characteristic rule as information (meta information meta) for restructuring the Web information. The Web information aggregating apparatus 1 uses the restructured information as a collected Web information classification or search key.

  FIG. 2 is a table illustrating the configuration of the vocabulary set list held in the vocabulary set list storage unit 4 (hereinafter referred to as a vocabulary set list table 21). Referring to FIG. 2, the vocabulary set list storage unit 4 uses a plurality of phrases that are considered to be related as a vocabulary set. The vocabulary set is a set in which attributes having the same meaning and different notation are included in meta information as a single category. The vocabulary set list storage unit 4 holds a vocabulary set and an aggregate word indicating the vocabulary set in association with each other.

  FIG. 3 is a table illustrating the configuration of attribute characteristic rules held in the attribute characteristic rule storage unit 5 (hereinafter referred to as attribute characteristic rule table 22). Referring to FIG. 3, the attribute characteristic rule storage unit 5 holds a plurality of constraint conditions as attribute characteristic rules. In the present embodiment, function rules, symmetry rules, transition rules, and the like can be defined as constraint conditions. For example, function rules uniquely determine the relationship between attributes and determine the existence conditions of dependent attributes. The symmetry rule indicates a condition that the function rules are mutually established between attributes. Further, the transition rule indicates a transition condition in which attribute A → attribute C is established if attribute A → attribute B and attribute B → attribute C among three or more attributes.

  For example, in a web news article, the technical development of a news category is defined as an attribute characteristic rule that is performed prior to the sales of news category products. In this case, even technology development related to the product is determined as not related to the product, and is used as a rule for selecting information. In addition, in the Web information of Company A and Company B, which are related to parts supply and receipt, the article on “Supply” seen from Company A has a constraint that it is symmetric with “Receiving” seen from Company B. It is defined as In this case, it is used as a rule for determining that both are semantically the same.

  FIG. 4 is a list illustrating the configuration of the meta information held in the meta information storage unit 12 in the present embodiment. FIG. 5 is a list illustrating the configuration of meta-meta information held in the meta-meta information storage unit 13 in the present embodiment.

  The operation of this embodiment will be described below. In the following, in order to facilitate understanding of the present invention, the operation of this embodiment will be described by taking as an example the case of conducting an industry structural analysis related to a personal computer product. In the operation of the present embodiment, the vocabulary set list and the attribute characteristic rule as described above are defined. FIG. 6 is a table illustrating a vocabulary set list in this case. FIG. 7 is a table illustrating the attribute characteristic rule in this case.

  FIG. 8 is a flowchart illustrating the operation of this embodiment. In step S <b> 101, the information collection unit 2 of the Web information aggregating apparatus 1 collects Web information published on the Internet that is considered to be related to a specific product, and stores it in the Web information storage unit 11. The information collecting unit 2 collects meta information accompanying the Web information and supplies it to the information determining unit 3.

  In step S102, the information determination unit 3 extracts the meta information supplied from the information collection unit 2 at this time, compares the attribute and attribute value with the vocabulary set list of the vocabulary set list storage unit 4, and matches them. It is determined whether or not to do. If there is no match as a result of the determination, the process ends. As a result of the determination, if there is a matching attribute and attribute value, the process proceeds to step S103.

  In step S103, the information determination unit 3 collates the supplied meta information with the attribute characteristic rule of the attribute characteristic rule storage unit 5, and determines whether or not they match. If there is no match as a result of the determination, the process ends. As a result of the determination, if there is a match, that is, if the attribute and the attribute value match both the vocabulary set list and the attribute characteristic rule, the process proceeds to step S104.

  In step S104, the information determination unit 3 creates, as meta-meta information, aggregate information that matches in the vocabulary set list, rules that match in the attribute characteristic rule, and link information to the stored Web information and meta information. In step S <b> 105, the information determination unit 3 regards the collected meta information as information related to the product, and stores the collected meta information and Web information in the information storage unit 6. The generated meta meta information is stored in the meta meta information storage unit 13 of the information storage unit 6.

  Thereafter, the information search unit 7 replaces the search request with the aggregated information and the attribute characteristic rule in response to the Web information search request. The information search unit 7 acquires all the meta-meta information that matches the aggregate information, the attribute, and the attribute characteristic rule from the information storage unit 6. Then, Web information is acquired from the link information of each meta-meta information and supplied to the transmission source of the search request. Thus, in the present embodiment, the meta information of the Web information is restructured with the meta meta information. Therefore, it is possible to easily extract Web information using the restructured data.

  The Web information aggregating apparatus 1 according to the present embodiment can extract keywords directly related to products such as parts supplier companies and product technologies in the product life cycle, including fluctuations in the notation, from the vocabulary set list. In addition, a service or the like indirectly related to a product can be extracted by the attribute characteristic rule. As a result, the Web information aggregating apparatus 1 according to the present embodiment can comprehensively collect information related to products.

  In other words, advocated by Michael Porter in Fig. 9 and widely recognized, there are five competitive factors analysis, opportunities and threats in SWOT analysis in Fig. 10, competition and market / customers in 3C analysis in Fig. 11, etc. Information necessary for analysis of factors can be exhaustively extracted.

  Further, the Web information aggregating apparatus 1 according to the present embodiment stores the aggregated information and the matched attribute characteristic rule as meta-meta information for each collected Web information. The Web information aggregating apparatus 1 according to the present embodiment can use this meta-meta information as a semantic search rule. Therefore, the Web information aggregating apparatus 1 according to the present embodiment can appropriately execute a semantic search such as extracting only information relating to a company and technology development related to component supply from the collected and stored information.

  For example, it is possible to search for information on distribution channels, search for technological trends, and search for increasing trends in alternatives / services. As an external environment analysis, Michael Porter in FIG. 10 competitive factor analysis, opportunity and threat in SWOT analysis in Fig. 10, 3C (Customer, Competitor, Company) analysis in Fig. 11 makes it easy to analyze factors such as competition and market / customer Because it becomes.

[Second Embodiment]
The second embodiment of the present invention will be described below. FIG. 12 is a block diagram illustrating a configuration of the Web information aggregation device 1 according to the second embodiment. The Web information aggregation device 1 of the second embodiment further includes an RSS information collection unit 14 and an RSS information analysis unit 15 in the configuration of the Web information aggregation device 1 of the first embodiment. The RSS information collection unit 14 stores a list of URLs of websites where RSS data is disclosed. RSS data is published for each website as a summary of a plurality of pieces of web information published on a website. The RSS information collection unit 14 accesses a website indicated by the stored URL, and stores RSS data collected from the website. The RSS information analysis unit 15 decomposes the RSS data stored in the RSS information collection unit 14 into meta information of individual Web information.

  The operation of the second embodiment will be described below. FIG. 13 is a flowchart illustrating the operation of the second embodiment. Referring to FIG. 13, in step S201, the RSS information collection unit 14 accesses a Web site indicated by the stored URL. The RSS information collection unit 14 supplies the RSS information analysis unit 15 with RSS data collected from a website that publishes web information that seems to be related to a specific product. In step S202, the RSS information analysis unit 15 receives the RSS data stored in the RSS information collection unit 14, and decomposes the RSS data into individual Web information and meta information.

  In step S203, the information collection unit 2 collects Web information based on link information to the text indicated in the meta information obtained by the RSS information analysis unit 15 performing the decomposition process. The information collecting unit 2 stores the collected Web information in the information storage unit 6.

  In step S204, the information determination unit 3 uses RSS data as meta information of Web information, collates the attribute and attribute value with the vocabulary set of the vocabulary set list storage unit 4, and the attribute and attribute value are the vocabulary set. It is determined whether or not it matches. If the result of the determination is that they do not match, the process ends. As a result of the determination, if there is a matching attribute and attribute value, the process proceeds to step S205.

  In step S <b> 205, the information determination unit 3 collates the meta information analyzed by the RSS information analysis unit 15 with the attribute characteristic rule of the attribute characteristic rule storage unit 5. The information determination unit 3 determines whether or not the meta information matches the attribute characteristic rule by the collation. If the result of the determination is that they do not match, the process ends. As a result of the determination, if there is something that matches the attribute characteristic rule, that is, if the attribute and the attribute value match both the vocabulary set list and the attribute characteristic rule, the process proceeds to step S206.

  In step S206, the aggregate information matched in the vocabulary set list, the rule matched in the attribute characteristic rule, and the stored Web information and link information to the meta information are generated. In step S207, the meta information is regarded as information related to the product, and the meta information and the Web information are stored in the information storage unit 6. Further, the meta-meta information generated in step S206 is stored in the information storage unit 6.

  In the second embodiment, the RSS information analysis unit 15 extracts meta information of individual Web information from Web site summary information. Therefore, even when meta information is not disclosed for each individual Web information, the Web information can be structured. The plurality of embodiments described above can be implemented in combination within a range in which there is no contradiction in the configuration and operation. In addition, the present invention is not limited to the above-described embodiment, and the information collection device that collects information related to a specific product from news articles and product information published on the Internet, and the information collection device are computers. It can be applied to uses such as a program for realizing the above. Also, the present invention can be applied to uses such as a search device and a program for realizing the search device on a computer.

FIG. 1 is a block diagram illustrating a configuration of a Web information aggregation device 1 according to the first embodiment. FIG. 2 is a table illustrating the configuration of the vocabulary set list. FIG. 3 is a table illustrating the configuration of the attribute characteristic rule. FIG. 4 is a list illustrating the configuration of the meta information held in the meta information storage unit 12 in the first embodiment. FIG. 5 is a list exemplifying a configuration of meta-meta information held in the meta-meta information storage unit 13 in the first embodiment. FIG. 6 is a table illustrating a specific configuration of the vocabulary set list. FIG. 7 is a table illustrating a specific configuration of the attribute characteristic rule. FIG. 8 is a flowchart illustrating the operation of the first embodiment. FIG. 9 is a block diagram showing five competitive factor analyses. FIG. 10 is a diagram showing opportunities and threats in the SWOT analysis. It is a figure which shows the structure in 3C analysis (Customer (customer), Competitor (competitor), Company (company)) of FIG. FIG. 12 is a block diagram illustrating a configuration of the Web information aggregation device 1 according to the second embodiment. FIG. 13 is a flowchart illustrating the operation of the second embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Web information aggregation apparatus 2 ... Information collection part 3 ... Information determination part 4 ... Vocabulary set list storage part 5 ... Attribute characteristic rule storage part 6 ... Information storage part 7 ... Information search part 11 ... Web information storage part 12 ... Meta information Storage unit 13 Meta-meta information storage unit 14 RSS information collection unit 15 RSS information analysis unit 21 Vocabulary set list table 22 Attribute property rule table

Claims (15)

A vocabulary set list storage unit for holding a vocabulary set list;
An attribute characteristic rule storage unit for holding attribute characteristic rules;
An information collection unit that collects web information and meta information attached to the web information;
An information determination unit that determines whether the Web information is information related to a target based on the collected meta-information;
The information determination unit
The attribute of the Web information specified based on the meta-information is compared with the vocabulary set list, and when the vocabulary set matching the attribute is included in the vocabulary set list, the attribute and the attribute characteristic rule are A Web information aggregating apparatus that collates and determines that the Web information corresponding to the meta information is information related to the target when the attribute matches the attribute characteristic rule. The Web information aggregation device according to claim 1, further comprising:
RSS (Rich Site Summary) information acquisition unit that collects RSS data from a website that publishes web information;
An RSS information analysis unit that extracts meta information of individual Web information from the RSS data;
The RSS information acquisition unit
Access the website, supply RSS data collected from the website to the RSS information analysis unit,
The RSS information analysis unit
Web information aggregating apparatus supplying the information collecting unit to the meta information obtained by decomposing the RSS data into individual Web information and meta information, and supplying the Web information obtained by the decomposition to the information determining unit . The Web information aggregation device according to claim 1 or 2,
The vocabulary set list includes a plurality of vocabulary sets;
Each of the plurality of vocabulary sets is
A Web information aggregating apparatus, which is a set of character strings indicating the attributes included in meta-information and having character strings having the same meaning and different notation as one category. The Web information aggregation device according to claim 3,
The attribute information rule indicates a constraint condition between different attributes. 5. The Web information aggregation device according to claim 4, further comprising an information search unit,
The information determination unit
When it is determined that the Web information is information related to the object,
Create link information to the Web information and meta information as meta meta information,
The information search unit
In response to the Web information search request,
A Web information aggregating apparatus that acquires the Web information based on link information of meta-meta information that matches the search request and supplies the Web information to a transmission source of the search request. A Web information aggregation program showing a procedure for causing a computer having a vocabulary set list storage unit for storing a vocabulary set list and an attribute characteristic rule storage unit for storing attribute characteristic rules to function as a Web information aggregation device,
(A) collecting web information and meta information accompanying the web information;
(B) determining whether the Web information is information related to a target based on the collected meta-information;
The step (b)
The attribute of the Web information specified based on the meta-information is compared with the vocabulary set list, and when the vocabulary set matching the attribute is included in the vocabulary set list, the attribute and the attribute characteristic rule are If the attribute matches the attribute characteristic rule, the computer functions as a Web information aggregating apparatus by a method including the step of determining that the Web information corresponding to the meta information is information related to the target Web information aggregation program. The Web information aggregation program according to claim 6, further comprising:
(C) collecting RSS (Rich Site Summary) data from a website that publishes web information;
(D) extracting meta information of individual Web information from the RSS data, and
The step (c) includes:
Accessing the website and supplying RSS data collected from the website;
The step (d) includes:
Supplying the information collection unit with the meta information obtained by decomposing the RSS data into individual Web information and meta information;
A Web information aggregating program for causing a computer to function as a Web information aggregating apparatus by a method including a step of supplying the Web information obtained by the decomposition to the information determination unit. The Web information aggregation program according to claim 6 or 7,
The vocabulary set list includes a plurality of vocabulary sets;
Each of the plurality of vocabulary sets is
In the character string indicating the attribute included in the meta information, when the character string having the same meaning and different notation is aggregated as one category,
A Web information aggregation program that causes a computer to function as a Web information aggregation device. The Web information aggregation program according to claim 8,
The attribute characteristic rule is a Web information aggregation program that causes a computer to function as a Web information aggregation device when a constraint condition between different attributes is indicated. The Web information aggregation program according to claim 9, further comprising:
(E) in response to a search request for Web information, comprising acquiring the Web information and supplying the Web information to a transmission source of the search request;
The step (b)
When it is determined that the Web information is information related to the object, a step of creating link information to the Web information and meta information as meta-meta information,
The step (e) includes:
In response to the Web information search request,
A Web information aggregating program for causing a computer to function as a Web information aggregating apparatus by a method of acquiring the Web information and supplying the Web information to a transmission source of the search request based on link information of meta-meta information matching the search request. (A) collecting web information and meta information accompanying the web information;
(B) determining whether the Web information is information related to a target based on the collected meta-information;
The step (b)
Collating the attribute of the Web information specified based on the meta information with the vocabulary set list read from the vocabulary set list storage unit;
When the vocabulary set matching the attribute is included in the vocabulary set list, the attribute and the attribute characteristic rule read from the attribute characteristic rule storage unit, and
A Web information aggregation method including a step of determining that the Web information corresponding to the meta information is information related to the target when the attribute matches the attribute characteristic rule. The Web information aggregation method according to claim 11, further comprising:
(C) collecting RSS (Rich Site Summary) data from a website that publishes web information;
(D) extracting meta information of individual Web information from the RSS data, and
The step (c) includes:
Accessing the website and supplying RSS data collected from the website;
The step (d) includes:
Supplying the information collection unit with the meta information obtained by decomposing the RSS data into individual Web information and meta information;
A Web information aggregation method comprising the step of supplying the Web information obtained by the decomposition to the information determination unit. The Web information aggregation method according to claim 11 or 12,
The vocabulary set list includes a plurality of vocabulary sets;
Each of the plurality of vocabulary sets is a set of character strings indicating the attributes included in the meta information, and a set of character strings having the same meaning and different notation as one category. Web information aggregation method. The web information aggregation method according to claim 13,
A Web information aggregation method in which the attribute characteristic rule indicates a constraint condition between different attributes. The Web information aggregation method according to claim 9, further comprising:
(E) in response to a search request for Web information, comprising acquiring the Web information and supplying the Web information to a transmission source of the search request;
The step (b)
When it is determined that the Web information is information related to the object, a step of creating link information to the Web information and meta information as meta-meta information,
The step (e) includes:
In response to the Web information search request,
A Web information aggregation method that acquires the Web information based on link information of meta-meta information that matches the search request and supplies the Web information to a transmission source of the search request.

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