International Business Machines Corporation

Rikiya Takahashi

Shoko Suzuki

Shohei Hido

Toshihiro Takahashi

Tsuyoshi Ide

Akira Tajima

Hisashi Kashima

Yuta Tsuboi

Sachiko Yoshihama

Karim Hamzaoui

A calculation apparatus includes a feature vector acquisition unit for acquiring a feature vector that corresponds to each alternative of a plurality of choice sets; an absolute evaluation calculation unit for calculating an absolute evaluation vector that represents an absolute evaluation of alternatives independent of a combination of the plurality of alternatives; a relativized-matrix calculation unit for calculating a relativized matrix that represents relative evaluations of the plurality of alternatives in a choice set; and a relative evaluation calculation unit for calculating a relative evaluation vector that represents a relative evaluation of each alternative of the plurality of alternatives from a product of multiplying the relativized matrix by the absolute evaluation vector. The calculation apparatus can predict intransitive choices of a person who exhibits intransitive preferences.

Calculation apparatus, calculation method, learning apparatus, learning method, and program

An analysis device including a substitution unit for substituting each event in an impulse-like event series with rectangular windows; a dividing unit for dividing the event series timewise at least at one transition point in the rectangular windows; a state vector generation unit for generating a state vector corresponding to the state of the rectangular windows in response to each of the divided time periods; and an analysis unit for performing Poisson regression using the state vectors corresponding to the time periods. A method comprising computer-executable steps is provided that substitutes each event in the inputted event series with rectangular windows; divides the event series timewise at least at one transition point in the rectangular pulses; generates a state vector corresponding to the state of the rectangular pulses in response to each of the divided time periods; and performs a Poisson regression using the state vectors corresponding to the time periods.

Analysis device, analysis program, analysis method, estimation device, estimation program, and estimation method

A method applied to a computer that determines a situation of a system includes the steps of: receiving measurement data from each of a plurality of measurement targets in the system; computing a plurality of sets of anomaly values based on the measurement data and a predetermined computation algorithm according to a plurality of classifications corresponding to a plurality of properties of each measurement target; and determining the situation of the system based on the sets of anomaly values and a predetermined determination algorithm.

Method, computer program, and computer for determining system situation

A method for clustering a plurality of data items stored in a computer includes calculating, with the computer, a plurality of components comprising kernels based on a distribution that gives similarity between the data items, wherein a non-negative mixture weight is assigned to each of the kernels; preparing a set of active components that are composed of subscripts of the mixture weights; applying operations to the set of active components; and determining whether the mixture weight has converged, and if not converged yet, reapplying the operations to the set of components, and if the mixture weight has converged, clustering the data items based on the mixture weight.

Clustering system, method and program

Location estimation systems, methods, and non-transitory computer program products. The system includes: storage means provided in the computer, means for storing the vector datasets in the storage means of the computer, means for calculating the similarity between the vector dataset without any location label and each neighboring vector dataset with a location label, by using any one of a q-norm where 0&#x2266;q&#x2266;1 and an exponential attenuation function, and means for estimating the location label of the vector data without any location label from the calculated similarities.

Location estimation system, method and program

A location estimation method using label propagation. The achieved location estimation method is robust to variations in radio signal strengths and is highly accurate by using the q-norm (0&#x3c;q&#x3c;1), especially, for calculating the similarities among radio signal strength vectors. The accuracy in location estimation is further improved by putting more importance on the time-series similarities. Specifically, the time-series similarity is calculated by using time-series values indicating the temporal order of radio signal strengths during the measurement. If the time-series similarity is larger than the similarity between the radio signal strength vectors, the time-series similarity is preferentially used. The exponential attenuation function can also be used for calculating the similarities, instead of the q norm (0&#x3c;q&#x3c;1).

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Kanagawa-ken, Japan

Rikiya Takahashi