Kabushiki Kaisha Toshiba

Toshiba Digital Solutions Corporation

Toshiba Solutions Corporation

Kazuyoshi Nishi

Shigeaki Sakurai

Shozo Isobe

Shigeru Matsumoto

Yasuyoshi Hyodo

Rumi Hayakawa

Kyoko Makino

Seiji Egawa

Taisuke Yamanaka

Hiroyuki Suzuki

Masaru Suzuki

Toshio Okamoto

Takashi Tanaka

Yoshikata Tobita

Toshiyuki Kano

Yoshimi Saito

Hideki Iwasaki

Saori Nitta

Nahoko Oshita

Koichi Kagawa

Shinichirou Amanashi

Yoshinori Masaoka

Disclosed is a service providing system capable of providing an information processing function effective for a variety of system constructions as a service. The service providing system of the present embodiment realizes an information retrieval function, a knowledge base construction function, and a knowledge presentation function. The information retrieval function retrieves information on an analysis target and information indicating a condition of the analysis target; the knowledge base construction function constructs a knowledge database for acquiring knowledge corresponding to the condition of the analysis target based on the information retrieved by the information retrieval function. The knowledge presentation function presents knowledge corresponding to the condition of the analysis target from the knowledge database.

Service providing system, business analysis support system, and method

According to one embodiment, a behavior estimating method for estimating behavior of a person being measured equipped with an activity meter including an acceleration sensor, includes presetting a first angle between a gravitation direction and a direction of action of a standard person being measured, calculating different acceleration waveforms from the activity meter, extracting a second angle between the gravitation direction and the direction of action of the person from the acceleration waveforms, performing a coordinate transformation process among the acceleration waveforms based upon the present first angle and the extracted second angle, and performing behavior estimation of the person using a result of the coordinate transformation.

Behavior estimating method, behavior estimating system, service providing method, signal detecting method, signal detecting unit, and signal processing system

An embodiment of a data pattern analysis optimizer includes a time sequence data memory, an estimator, a grouping unit, and a time sequence pattern extractor. The time sequence data memory stores a plurality of time sequence data made from items in time order. The estimator estimates the upper limit of the total number of types of time sequence patterns present in the time sequence data at a rate higher than a minimum support level, based on a respective rate of presence of each item, wherein each of the time sequence patterns present in the time sequence data is a predefined number of items. In case that the estimated upper limit exceeds an upper limit of the number of types of time sequence patterns as a maximum processing load to a computer, the grouping unit groups a plurality of time sequence data into sub-groups, based on a group of items having the increased number of items and gives the estimator instructions to perform estimation. The time sequence pattern extractor gives the computer instructs to extract the time sequence patterns for each of the sub-groups, in case that the estimated upper limit does not exceed the upper limit of the number of time sequence patterns.

Data pattern analysis optimizer, and method of data pattern analysis optimization processing

According to one embodiment, an operation estimating method comprises presetting a plurality of operation candidates to be estimated, acquiring acceleration data from an activity meter worn by a person being measured, calculating estimated probabilities of the operation candidates from the acquired acceleration data, selecting an operation candidate corresponding to a maximum probability from the calculated estimated probabilities, as an estimated operation, and correcting the estimated operation in consideration of a past operation performance when the maximum probability of the estimated probabilities is lower than a predetermined value.

Operation estimating method and operation estimating system

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

Provided is a knowledge extracting apparatus for extracting knowledge information related to a knowledge-extraction target from an electronic document distributed continually in a state where the electronic document is not associated with the knowledge-information extraction target. A knowledge extracting apparatus according to one embodiment is a knowledge extracting apparatus including: an information receiving section for receiving an electronic document; a knowledge extracting section for extracting a concept from the electronic document based on a target word to extract knowledge information and a clue word to extract knowledge information and forming knowledge information in which the concept thus extracted and the target word are associated with each other; a storage section for storing the knowledge information thus extracted; and an information analysis section for, after the knowledge information is stored, analyzing the electronic document based on the knowledge information in the storage section.

Forming knowledge information based on a predetermined threshold of a concept and a predetermined threshold of a target word extracted from a document

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Fuchu, Japan

Kazuyoshi Nishi