Fujitsu Corporation

Tetsuro Takahashi

Kanji Uchino

Seishi Okamoto

Jun Zhang

Hiroko Suzuki

Tadanobu Furukawa

A population formation method is disclosed. Keywords are extracted from public information of providers included as elements in a first provider group. Each element is calculated based on a predetermined attribute value. A first attribute is for the providers of the public information. The attribute value is changed with time. Each of rules set for duplicate keywords is to determine one of the attributes by using one of the duplicate keywords. Provider groups are formed for new public information based on the duplicate keywords and the rules. A provider group having a similar relationship with a first provider group is specified by a distribution of the attribute value of a different attribute from the first attribute. A new provider group corresponding to the first provider group is formed by the providers, for whom the attribute value of the first attribute corresponds to the predetermined attribute value.

Population formation method, population formation apparatus, and computer-readable recording medium

According to an aspect of an embodiment, a method may include obtaining a wordlist from a digital document. The method may further include creating a keyword candidate list derived from the wordlist and noting the relationships between the keyword candidates. The method may also include obtaining scores for the keyword candidates. The method may further include selecting keyword candidates as keywords of the digital document based on the scores and the relationships between the keyword candidates.

Digital document keyword generation

A data classification method which classifies a plurality of data into a plurality of classification items based on a feature quantity included in the data, the method includes calculating, by a processor, an appearance probabilities in which training data including the feature quantity appears in the classification items in a distribution of the data, generating, by the processor, a rule having the feature quantity and a weighting of the feature quantity based on a plurality of the training data having the feature quantity based on the appearance probabilities; and classifying, by the processor, the plurality of data according to the rule.

Data classification method, storage medium, and classification device

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.

Method and system for keyword management

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.

Keyword output apparatus and method

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. An evaluation pair extraction unit gives an evaluation pair extracted from a model document to a machine leaner to cause it to learn a rule which can serve as an evaluation pair, and, after the learning, correctly combines an object with an evaluation expression from an unknown document to extract an evaluation pair.

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Kawasaki, Japan

Tetsuro Takahashi