Abstract: This invention is to appropriately support creation of a classification rule for a new data item. This method includes: storing a new data item and a category of the new data item into a storage; extracting feature patterns each including a condition including a feature element of the new data item stored in the storage and a corresponding category from data stored in a correct answer data storage, which stores data items and categories of the data items, and storing the feature patterns into a feature pattern storage; and grouping the feature patterns stored in the feature pattern storage into a first set whose feature pattern matches with the category of the new data item stored in the storage and a second set whose feature pattern does not match with the category of the new data item, and storing a grouping result into a group data storage.

Abstract: This invention is to automatically extract noteworthy information from a large amount of information. First, a disclosure unit of an individual opinion such as a statement in a personal Web page or a bulletin board is extracted from collected content information, and information such as URL or statement number for specifying the disclosure unit of the individual opinion is registered. Next, an object such as company name or industry type of the individual opinion is specified. Then, the disclosed contents of the individual opinion are analyzed, so that an evaluation as to the object such as good evaluation or bad evaluation is specified. Besides, the reliability is determined based on referenced degree ranking and based on whether information to indicate the basis of the opinion or the identity of the speaker is included. Thus, the evaluation as to the object as characteristics of the individual opinion can be presented to requesters.

Abstract: Related keywords having certain relations to a target keyword are extracted from a unit storing keywords according to relations among each other. Expressions corresponding to the target keyword and related keywords are read from a unit storing expressions correspondingly with each stored keyword, each expression having been extracted from a content containing the corresponding keyword. A commonness between the expressions corresponding to each related keyword and the target keyword is calculated. An association between each related keyword and the target keyword is calculated using a distance for each related keyword from the target keyword and the commonness. A related keyword having a certain association is extracted as a same-region keyword in a same region as the target keyword. A drawing including the target keyword and related keywords arranged according to the associations is output with the same-region keyword displayed distinguishably from other related keywords not included in the same region.

Abstract: A keyword management system for managing keywords used when a user terminal connected to a network accesses contents, includes a Burst value calculating unit that calculates a Burst value indicating an increase per unit time of a keyword, an overall Burst value calculating unit that calculates an overall Burst value by correcting the Burst value based on characteristics in the contents of the keyword corresponding to the Burst value, and an output controlling unit that extracts from the contents, a relevant keyword related to the keyword corresponding to the overall Burst value based on time series changes of the overall Burst value, and outputs the keyword and the relevant keyword associated with each other to the user terminal.

Abstract: An evaluation pair extraction unit analyzes a document which is present on a network to extract an evaluation pair composed of an object and an evaluation expression, and registers it in an evaluation pair database. An evaluation pair analysis unit executes analysis such as category estimation, specific evaluation expression extraction, and comparative analysis by utilizing the evaluation pair of the database. The evaluation pair is data in which the object and the evaluation expression are combined; wherein the object is a unique object including a commercial product name, maker name, or the like which can be evaluated, and the evaluation expression of the evaluation pair is a phrase representing evaluation including like, hard to use, or the like.

Abstract: An advertisement page on which an article written by an advertiser are sorted from web pages that are used for posting articles on the Internet. A word list is prepared in which words including unique expressions are registered. Words are extracted from text information included in the web pages, a number is counted indicating how many words match between the words contained in the word list and the extracted words, and the advertisement page is sorted out from the web pages based on the count.

Abstract: An evaluation pair extraction unit analyzes a document which is present on a network to extract an evaluation pair composed of an object and an evaluation expression, and registers it in an evaluation pair database. An evaluation pair analysis unit executes analysis such as category estimation, specific evaluation expression extraction, and comparative analysis by utilizing the evaluation pair of the database. The evaluation pair is data in which the object and the evaluation expression are combined; wherein the object is a unique object including a commercial product name, maker name, or the like which can be evaluated, and the evaluation expression of the evaluation pair is a phrase representing evaluation including like, hard to use, or the like.

Abstract: This invention is to appropriately support creation of a classification rule for a new data item. This method includes: storing a new data item and a category of the new data item into a storage; extracting feature patterns each including a condition including a feature element of the new data item stored in the storage and a corresponding category from data stored in a correct answer data storage, which stores data items and categories of the data items, and storing the feature patterns into a feature pattern storage; and grouping the feature patterns stored in the feature pattern storage into a first set whose feature pattern matches with the category of the new data item stored in the storage and a second set whose feature pattern does not match with the category of the new data item, and storing a grouping result into a group data storage.

Abstract: A category setting support method according to this invention includes calculating an influence degree to carry out a category setting to a data item for each of a plurality of data items stored in a data storage based on a predetermined relevant item, and storing the influence degree into the data storage in association with the corresponding data item; and determining a category setting priority order for each data item based on the influence degrees stored in the data storage, and displaying a display to carry out the category setting based on the category setting priority order. Accordingly, it becomes possible for a user such as a system administrator to efficiently set a category to the data item.

Abstract: A group of documents in a forum/message board are stored as a document group database in a predetermined server computer. A document group analysis device analyzes a group of documents contained in each set of documents corresponding to each message board in the document group database. A summation device generates a meta-index, a thread index, and an indexed file. A display device displays a group of documents in a display format of a keyword view, a thread view, or an author view using a meta-index and a thread index.

Abstract: The information categorizing apparatus comprises a feature element extraction section which extracts a feature element for each categorizing category from a plurality of sample texts included in the categorizing sample data in which a sample text group and a plurality of categories are associated with each other in advance. Further, a categorizing method determination section determines a categorizing method based on the categorizing sample data. A categorizing learning information generation section generates categorizing learning information representing a feature for each category, based on the extracted feature elements, in accordance with the determined categorizing method. An automatic categorizing section categorizes a new text group to be categorized for each category, in accordance with the determined categorizing method and the categorizing learning information.

Abstract: This invention is to automatically extract noteworthy information from a large amount of information. First, a disclosure unit of an individual opinion such as a statement in a personal Web page or a bulletin board is extracted from collected content information, and information such as URL or statement number for specifying the disclosure unit of the individual opinion is registered. Next, an object such as company name or industry type of the individual opinion is specified. Then, the disclosed contents of the individual opinion are analyzed, so that an evaluation as to the object such as good evaluation or bad evaluation is specified. Besides, the reliability is determined based on referenced degree ranking and based on whether information to indicate the basis of the opinion or the identity of the speaker is included. Thus, the evaluation as to the object as characteristics of the individual opinion can be presented to requesters.

Abstract: This invention is to automatically extract noteworthy information from a large amount of information. First, a disclosure unit of an individual opinion such as a statement in a personal Web page or a bulletin board is extracted from collected content information, and information such as URL or statement number for specifying the disclosure unit of the individual opinion is registered. Next, an object such as company name or industry type of the individual opinion is specified. Then, the disclosed contents of the individual opinion are analyzed, so that an evaluation as to the object such as good evaluation or bad evaluation is specified. Besides, the reliability is determined based on referenced degree ranking and based on whether information to indicate the basis of the opinion or the identity of the speaker is included. Thus, the evaluation as to the object as characteristics of the individual opinion can be presented to requesters.

Abstract: The information categorizing apparatus comprises a feature element extraction section which extracts a feature element for each categorizing category from a plurality of sample texts included in the categorizing sample data in which a sample text group and a plurality of categories are associated with each other in advance. Further, a categorizing method determination section determines a categorizing method based on the categorizing sample data. A categorizing learning information generation section generates categorizing learning information representing a feature for each category, based on the extracted feature elements, in accordance with the determined categorizing method. An automatic categorizing section categorizes a new text group to be categorized for each category, in accordance with the determined categorizing method and the categorizing learning information.

Abstract: A group of documents in a forum/message board are stored as a document group database in a predetermined server computer. A document group analysis device analyzes a group of documents contained in each set of documents corresponding to each message board in the document group database. A summation device generates a meta-index, a thread index, and an indexed file. A display device displays a group of documents in a display format of a keyword view, a thread view, or an author view using a meta-index and a thread index.