Abstract: There is provided with a monitoring method of monitoring plural apparatuses each having a sensor, including: selecting two or more sample apparatuses out of the plural apparatuses; calculating averages and standard deviations of sensor values detected by the sample apparatuses for each sample apparatus; calculating a confidence interval of the averages and an average of the standard deviations; and calculating an average of sensor values detected by an arbitrary apparatus among the plural apparatuses as an object average and calculating a normal range of the sensor of the arbitrary apparatus from the object average, the confidence interval, and the average of the standard deviations.

Abstract: A data analyzing system includes an input-output device, a plurality of local analyzing devices, a center analyzing device and a connecting device which connects between the input-output device, the local analyzing devices, and the center analyzing device. The connecting device may receive and execute a forwarding setting command from the input-output device to select and set one or more devices, to which the command from the input-output device should be forwarded, from the local analyzing devices and the center analyzing device and forward a command different from the forwarding setting command transmitted from the input-output device to the devices, in which forwarding is set, and forward data or command transmitted from the local analyzing devices and the center analyzing device, in accordance with destinations described in the data or the command.

Abstract: There is provided with a data recording apparatus including: an observed data storage configured to store values observed by a sensor in association with an observed time; an intersection processing unit configured to plot each observed value in the observed data storage on a plane coordinate system formed by a time axis and an axis representing a value of the sensor, configured to determine whether or not a line segment connecting between observed values at adjacent times intersects a base line preset on the plane coordinate system and configured to calculate an intersection time of the line segment and the base line when the line segment intersects the base line; an intersection data storage configured to store the intersection time calculated by the intersection processing unit; and a deleting unit configured to delete observed values subjected to a processing of the intersection processing unit from the observed data storage.

Abstract: There is provided with a monitoring method of monitoring plural apparatuses each having a sensor, including: selecting two or more sample apparatuses out of the plural apparatuses; calculating averages and standard deviations of sensor values detected by the sample apparatuses for each sample apparatus; calculating a confidence interval of the averages and an average of the standard deviations; and calculating an average of sensor values detected by an arbitrary apparatus among the plural apparatuses as an object average and calculating a normal range of the sensor of the arbitrary apparatus from the object average, the confidence interval, and the average of the standard deviations.

Abstract: There is provided with a clustering apparatus including: an initial cluster generator configured to divide multi-dimensional data to generate a plurality of clusters each including one or more data pieces; a cluster recorder configured to record the clusters generated; a cluster selector configured to calculate parameters of a previously given model which is common to the clusters, from each of the clusters, and select clusters to be unified on the basis of the parameters calculated from each cluster; a cluster unifier configured to unify clusters selected by the cluster selector to generate a new cluster; and a cluster evaluator configured to calculate an evaluation value for evaluating a set of the clusters except the unified clusters and the new cluster.

Abstract: According to an aspect of the present invention, there is provided with a data division apparatus which divides multi-dimensional data, including: a data input unit which inputs multi-dimensional data; a division plane candidate creator which creates a plurality of division plane candidates for dividing the multi-dimensional data; a data provisional division unit which provisionally divides the multi-dimensional data by using the division plane candidate to generate clusters; a model generator which generates models from the clusters; an evaluation value calculator which calculates an evaluation value on the basis of the generated models and the multi-dimensional data; a division candidate selector which compares evaluation values respectively corresponding to the division plane candidates and selects a division plane candidate having a highest evaluation value; and a data division unit which divides the multi-dimensional data by using the selected division plane candidate.

Abstract: A spatial data analysis apparatus includes a storage configured to store a record group of records each including a multi-dimensional spatial attribute containing a place and a description attribute regarding the spatial attribute; a divider configured to divide the record group into a plurality of virtual record groups corresponding to a plurality of places according to each of a plurality of conditions determined by the description attribute; a calculator configured to calculate a degree of spatial dispersion of records of each of the plurality of virtual record groups in the places to obtain a plurality of degrees of dispersion; and a selector configured to select from the conditions a condition corresponding to a virtual record group that indicates a lowest degree of dispersion among the degrees of dispersion.

Abstract: A data analyzing apparatus that stores geographic information and observation data including various information regarding an event. A data processing unit generates analyzing data by using the geographic information and the observation data, and a data analyzing unit derives a tendency of occurrence of the event based on the analyzing data. A prediction unit predicts a place where the tendency of occurrence of the event is high by using the tendency and the geographic information. An observation data input unit inputs new observation data, and an analyzing monitor unit controls the data processing unit to generate modified analyzing data by using the new observation data, the observation data and the geographic information, and readjusts the analyzed result based on the modified analyzing data. A health condition observer observes a health condition data, and the observation data input unit inputs the observation data including the health condition data.

Abstract: There is provided with a data analysis method including: reading out, from a database which is a set of records each including plural explanation variables and a target variable, the target variables of the records; generating a first plurality of clusters based on the read target variables of the records; determining to which cluster each record belongs; generating a classification rule for predicting a cluster from explanation variables; storing the generated classification rule; selecting an explanation variable referred to in the generated classification rule; storing the selected explanation variable in an explanation variable list; and generating a second plurality of clusters based on explanation variables in the records on the explanation variable list and the target variables of the records.

Abstract: There is provided a data processing apparatus including: a classification rule generation unit that generates a classification rule having a plurality of partial rules, using a set of records each record including a plurality of attribute values; a partial rule selection unit that selects a partial rule whose classification accuracy does not satisfy a predetermined standard; a record detection unit that detects records which accord with a conditional part of the selected partial rule from among the set of records; an additional attribute decision unit that decides a additional attribute to be newly added; a retrieval request unit that requests a retrieval system to retrieve attribute values of the detected records for the additional attribute; and a partial rule regeneration unit that regenerates a partial rule for replacing the selected partial rule, using the attribute values for the additional attribute retrieved by the retrieval system.

Abstract: This apparatus, method, and program, from a plurality of records each record including position information showing a position in a two or more-dimensional space and a plurality of attribute information pieces, finds a condition of attribute information under which records are congested in the space, including: selecting records having same attribute information piece from the plurality of records for each of attribute information pieces; storing the attribute information piece in case where the records selected satisfy a predetermined congestion condition based on the position information of the records selected; combining attribute information pieces stored among different attributes to generate a combination of attribute information pieces; selecting records having the combination of attribute information pieces from the plurality of records; and storing the combination of attribute information pieces in case where the records selected satisfy the predetermined congestion condition based on the position in

Abstract: An inverse model calculation apparatus and method according to an embodiment of the present invention record an input value inputted sequentially to a target system and an output value outputted sequentially from the target system as time series data, generate a decision tree for inferring an output value at future time, using the time series data, detect a leaf node having an output value at future time as a value of an object variable from the decision tree, and acquire a condition of explaining variables included in a rule associated with a path from a root node of the decision tree to the detected leaf node, as a condition for obtaining the output value.

Abstract: A data analyzing apparatus, comprising: a first storage which stores geographic information, a second storage which stores observation data including contents of an event, a position where the event occurred and a time when the event occurred, a data processing unit configured to generate analyzing data by using the geographic information and the observation data, a data analyzing unit configured to derive a tendency of occurrence of the event based on the analyzing data, and a prediction unit configured to predict a place where the tendency of occurrence of the event is high by using the analyzing result and the geographic information.

Abstract: A data prediction method using a computer including a first memory which stores a rule showing the relationship between observation data obtained by observing an event in a first region and first attribute data representing geographical features at the observation point of the event; and a second memory which stores geographical information data on a second region different from the first region, comprises:

Abstract: A spatial data analysis apparatus comprises a receiving unit that generate a record group of records each including a multi-dimensional spatial attribute and a description attribute regarding the spatial attribute, a virtual division unit that divides the record group according to a first division condition determined by the description attribute to generate a plurality of virtual record groups, and a determination unit that computes a degree of spatial dispersion of records of each of the plurality of virtual record groups and determines a second division condition and a virtual record group that indicate a lowest degree of dispersion.