Abstract: An extracted hypothesis has logical formulas leading to a possible conclusion. If the logical formulas include one including a first parameter a value obtained from observation data and a second parameter that does not have a value obtained from the observation data, the logical formula is set as a target logical formula, and a value of the second parameter acquired based on the observation data is input. If there is no such logical formula, but there is a logical formula that has, for one or more parameters, a value set in advance or obtained using inference knowledge, whether this logical formula is true or false is determined. When whether the logical formula is true or false is determined, or, when the value of the second parameter is input, the logical formula is added to the observation data, and a hypothesis is derived again.

Abstract: The information search apparatus 100 includes: a logical inference unit 10 that executes a logical inference by applying a rule indicating a relationship between occurrences to a set of data indicating observed occurrences, and generates data of a series of occurrences through the logical inference; a query generation unit 20 that determines a condition for extracting data related to the series of occurrences from the set of data indicating observed occurrences based on the data of the series of occurrences and the rule indicating a relationship between occurrences, and generates a query using the condition determined; and a data search unit 30 that executes search processing on the set of data indicating observed occurrences using the query generated.

Abstract: In an inference device, an acquisition means acquires first observation data and first knowledge base which is formed by a rule representing a pair of a premise and a consequence of the premise. A rule conversion means reverses the premise and the consequence of the rule forming the first knowledge base, and generates a second knowledge base formed by a rule deriving the premise from the consequence. An inference execution means executes an abductive inference using the second knowledge base and the first observation data, and generates a first hypothesis set represented by a directed graph. A data extraction means extracts an element serving as a starting point in the directed graph representing the first hypothesis set, and generates second observation data. Accordingly, the inference execution means executes the abductive inference by using the first knowledge base and the second observation data, and generates a second hypothesis set.

Abstract: An inferential knowledge construction support apparatus 1 has a literal generation unit 2 that generates literal information based on the extracted elements, a rule generation unit 3 that estimates a causal or implicational relation between literals, using plural pieces of literal information, and generates rule information by allocating literal information estimated to be in the causal/implicational relation to an antecedent and a consequent, a display information generation unit 4 that generates display information to be used for causing a display device to output a rule editing user interface for displaying, in a juxtaposed manner, a literal display area for displaying the literal information and descriptive information corresponding to the literal information and a rule display area for displaying the rule information and descriptive information corresponding to the rule information, and an editing unit 5 that enables an operator to edit the rule information, using the rule editing user interface.

Abstract: An action plan estimation apparatus 10 includes: an information acquisition unit 11 that acquires an operation log indicating an operation and a context information indicating a status of the operation for each operation performed by a software on a computer system, a group generation unit 12 that divides each of the operation logs into groups based on a similarity between the context information, an action plan estimation unit 13 that executes abduction for each group by applying knowledge data indicating a relationship between an action plan executed by the software and an operation of the software to the operation log included in the group, and uses the result of the abduction to estimate an action plan to reach a preset target state, that is executed by the software from which the operation log is acquired, based on the operation indicated by the operation log included in the group.

Abstract: A data reduction apparatus 10 is an apparatus for reducing a data amount, targeting data having one or more attributes represented by a readable name. The data reduction apparatus 10 includes an attribute classification unit 11 that classifies an attribute of the target data by type based on attribute classification information specifying a subject identification attribute for identifying a subject of an event and a state attribute representing a temporary state or mode of the subject; and an attribute integration unit 12 that, if there are two or more attributes classified as the subject identification attribute as a result of the classification by the attribute classification unit, integrates the two or more attributes classified as the subject identification attribute into one attribute.

Abstract: A hypothesis verification apparatus 10 includes a hypothesis generation unit 11 that derives, from observation data expressed by a set of logical formulas each including one name and one or more parameters, a hypothesis made up of the logical formulas that lead to a possible conclusion, using knowledge data expressed in the same format as the observation data, and a hypothesis verification unit 12 that, if the logical formulas that make up the hypothesis include a logical formula that includes a first parameter that has a value obtained from the observation data and a second parameter that does not have a value obtained from the observation data, sets the logical formula as a target logical formula, acquires a value of the second parameter based on the observation data and a name of the target logical formula, and inputs the obtained value of the second parameter to the target logical formula, and if there is no logical formula that is to be set as the target logical formula, and if there is a logical formula

Abstract: Provided is a knowledge acquisition device for acquiring knowledge for performing reasoning taking into account characteristics of persons. A knowledge acquisition device 100 includes an acquisition unit 120 and an update unit 130. The acquisition unit 120 acquires knowledge representing a relationship between events relating to persons. The update unit 130 identifies, based on an attribute value possessed by each of a plurality of persons, an attribute value possessed by a person for whom the knowledge holds true among the plurality of persons. The acquisition unit 120 updates the knowledge in such a way that the updated knowledge holds true for a person having the identified attribute value, and outputs the updated knowledge.

Abstract: An inference-use knowledge generation apparatus 10 includes a data extraction unit 11 configured to extract, based on a set parameter, data corresponding to a designated position or region from a first data set including data regarding a stuff in a predetermined space in order to generate inference-use knowledge that is to be used in an inference that is made by a calculating machine, and a knowledge generation unit 12 configured to specify, from a second data set that includes a plurality of entities that form the space and have been grouped into groups of related entities, a group of entities described by words included in data that was extracted previously, and to generate inference-use knowledge indicating a spatial relationship between entities based on the specified group and a term expressing a preregistered spatial relationship.

Abstract: Provided is an information processing system to accurately predict performance of a classifier to the number of samples of labeled data. A training system 100 includes an extraction unit 120 and an estimation unit 130. The extraction unit 120 extracts a reference data set that is similar to a target data set, from one or more reference data sets. The estimation unit 130 estimates a performance of a classifier assuming that the classifier is trained with labeled data in the target data set, by using the extracted reference data set, and outputs the estimated performance.

Abstract: An event processing device includes: an event detection unit that, when received data satisfies predetermined conditions, detects the data as an event; a data storage unit that, irrespective of the event detection result, stores data received by the event detection unit; a relevance information definition storage unit that stores relevance information definitions that define the association between data; an integrated analysis unit that, when data is newly stored in the data storage unit, links the newly stored data with past data included in the past data stored in the data storage unit and the relationship of which with the newly stored data satisfies the relevance information definition; and an event display unit that displays the newly stored data and the past data linked with each other.

Abstract: A numeric range search device includes: interval index storage means for storing, for numeric ranges to be searched, an interval index that is made up of records each including at least an interval filter and reference information and in which the records are organized in units of records whose interval filters are at least partially common, the interval filter being data indicating a correspondence relationship between an input numeric value or numeric range and subintervals obtained by dividing a range including all of the numeric ranges by a predetermined boundary value, and the reference information being information for referring to a numeric range to be searched; interval query generation means for generating an interval query which is data indicating a correspondence relationship between the input numeric value or numeric range and the subintervals; and candidate selection means for selecting, from the records, a record for which an AND of an interval filter included in the record and the interval quer

Abstract: The present invention provides a color description analysis device which converts a natural language description as a description regarding colors expressed in a natural language into data representing distribution of values in a prescribed color space, comprising color ratio determining means which determines the ratio of each area occupied by each color included in the natural language description in the whole area of an image as the object of the natural language description by use of words and phrases indicating relationship between colors and included in the natural language description.

Abstract: An event processing device includes: an event detection unit that, when received data satisfies predetermined conditions, detects the data as an event; a data storage unit that, irrespective of the event detection result, stores data received by the event detection unit; a relevance information definition storage unit that stores relevance information definitions that define the association between data; an integrated analysis unit that, when data is newly stored in the data storage unit, links the newly stored data with past data included in the past data stored in the data storage unit and the relationship of which with the newly stored data satisfies the relevance information definition; and an event display unit that displays the newly stored data and the past data linked with each other.

Abstract: A data classifier system of the present invention selects a plurality of classifications correlated to data groups so as to output classification axes based on hierarchical classifications and data groups. The data classifier system includes a basic category accumulation means, a classification axis candidate creation means and a priority calculation means. The basic category accumulation means accumulates classifications serving as basic categories used for selecting desired classifications in advance. The classification axis candidate creation means creates classification axis candidates based on combinations of classifications each correlated to at least one data among descendant classifications of each basic category. The priority calculation means calculates priorities with respect to the classification axis candidates created by the classification axis candidate creation means based on hierarchical distances of classifications in the classified hierarchy.

Abstract: A data classifier system of the present invention selects a plurality of classifications correlated to data groups so as to output classification axes based on hierarchical classifications and data groups. The data classifier system includes a basic category accumulation means, a classification axis candidate reduction means and a priority calculation means. The basic category accumulation means accumulates classifications serving as basic categories used for desired classifications in advance. The classification axis candidate reduction means selects a plurality of classifications from among classifications descendant from each basic category so as to create classification axis candidates, thus reducing classification axis candidates subjected to calculations based on data quantity of classifications and hierarchical distances of classifications.

Abstract: The present invention is capable of accurately and easily extracting a failure and a cause of occurrence of the failure on the basis of past cases.

Abstract: Provided is an event processing device capable of eliminating an inconsistency between events in sequential processing in complex event processing of taking input events acquired from many origination sources. The event processing device 50 includes the event data storage means 51 for storing a set of event data mutually associated under a predetermined condition until a predetermined holding deadline, the event evaluation means 52 for, when newly-input event data meets the predetermined condition, including the event data as new event data in the set, and the event competition elimination means 53 for, when new event data is competitive data in which a competition is caused in attribute values for a common attribute with other event data included in the set, excluding the competitive data from the set.

Abstract: The present invention does not simply extract all situations likely to become problems without any criteria; from among situations mentioned within text, the invention detects situations that a writer particularly considers to be a problem. From text for which detection is to be performed, descriptions representing events mentioned in the text are extracted in units of situations for each of the events. From among the extracted situations, a situation that the writer who has described the situation assumes to be a situation that actually occurs, and/or a situation that is not an ancillary explanatory description, is sorted out as a situation in which the writer has interest. From among the sorted out situations, a situation that includes at least one expression that may become a problem is output as a problem situation.

Abstract: A table record estimation device includes: a table element string extraction unit having a function of extracting text data from input data and acquiring a series of keywords as an element of a table (table data) from the extracted text data; a table element labeling unit having a function of labeling the individual keywords acquired by the table element string extraction unit for each type based on correspondence information stored in a classification rule storage unit; and a label appearance pattern estimation unit having a function of estimating a label permutation constituting one-unit record from a label string attached for the each type by the table element labeling unit and outputting the label permutation as a record estimation result.