Kabushiki Kaisha Toshiba

Toshiba Solutions Corporation

Seiji Egawa

Shigeaki Sakurai

Shozo Isobe

Shigeru Matsumoto

Rumi Hayakawa

Kazuyoshi Nishi

Kazuyuki Goto

Yasunari Miyabe

Kyoko Makino

Hideki Iwasaki

Saori Nitta

According to one embodiment, a document analysis apparatus is an apparatus comprising first document storage circuit for storing first documents that include words, belong to respective categories constituting a hierarchical structure, and only comprise opinion documents for a desirable object, and a second document storage circuit for storing second documents that include words, belong or do not belong to the categories constituting the hierarchical structure and comprise opinion documents for the desirable object and documents other than the opinion documents, and the apparatus is configured to classify, into one of the categories constituting the hierarchical structure, the second documents that do not belong to the respective categories among the second documents stored in the second document storage circuit.

Document analysis apparatus and document analysis program

A data analysis supporting apparatus according to an embodiment comprises a variable-type determining device, a variable-variation generating device, and a variable-contribution rate determining device. The variable-type determining device determines the type of each variable. The variable-variation generating device generates variations of each variable in accordance with the variable type determined and with a variable variation rule that defines a method of generating the variations of each variable of any type. The variable-contribution rate determining device calculates the rate at which the variations and analysis data contribute to the objective variable, and determines, from the rate, whether the variations should be used or deleted.

Data analysis supporting apparatus

A data analyzing apparatus of an embodiment generates a format variation, analytical algorithm name, and analytical parameter not stored in a first storage device, and executes analysis. The data analyzing apparatus determines whether the application accuracy is lower than the knowledge model accuracy. If the determination result is 'not lower', the data analyzing apparatus reactivates a format variation generating device and an analytical parameter generating device. If the determination result is 'lower', the data analyzing apparatus reads out a format variation and knowledge model name associated with the highest priority order in the first storage device, and executes analysis.

Data analyzing apparatus and program

A pattern extracting apparatus includes a first storing section storing plural target information pieces, a candidate pattern producing section producing candidate patterns each including two or more items different from each other based on each of the items included in the plural target information pieces, a candidate evaluation value calculating section calculating an extraction evaluation value of the candidate pattern based on a frequency of appearance at which the produced candidate pattern appears in the plural target information pieces, a pattern extracting section determining and extracting any of the candidate patterns having the calculated extraction evaluation value satisfying a predetermined threshold value, and a second storing section storing an association degree between the items. The candidate evaluation value calculating section calculates the extraction evaluation value based on a weight based on an identified association degree between the items included in the candidate pattern and the frequency of appearance.

Pattern extracting apparatus and method

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Fuchu, Japan

Seiji Egawa