Abstract: A textual entailment recognition apparatus (2) includes a vector generation unit (21) that generates, for each of first and second texts, a vector for each predicate-argument structure by using a word other than a word indicating a type of argument of a predicate in the predicate-argument structure; a combination identification (22) unit that compares the vector generated for each predicate-argument structure for the first text and the vector generated for each predicate-argument structure for the second text, and identifies combinations of the predicate-argument structures of the first text and the predicate-argument structure of the second text based on a result of the comparison; and an entailment determination unit (23) that obtains a feature amount for each of the identified combinations, and determines whether the first text entails the second text based on the obtained feature amounts.

Abstract: An information analysis apparatus that performs an analysis on text information to determine whether or not the text information corresponds to the target information. The information analysis apparatus includes a storage device that stores the text information; a density estimation unit that estimates, in units of analysis each composed of a plurality of sentences of text information, a density indicating the degree to which the target information is included in the unit of analysis; and a determination unit that obtains an evaluation value indicating the degree to which each sentence included in each unit of analysis corresponds to the target information from the estimated density of the unit of analysis, and determines whether or not the sentence corresponds to the target information based on the evaluation value.

Abstract: A textual entailment recognition apparatus (2) includes a vector generation unit (21) that generates, for each of first and second texts, a vector for each predicate-argument structure by using a word other than a word indicating a type of argument of a predicate in the predicate-argument structure; a combination identification (22) unit that compares the vector generated for each predicate-argument structure for the first text and the vector generated for each predicate-argument structure for the second text, and identifies combinations of the predicate-argument structures of the first text and the predicate-argument structure of the second text based on a result of the comparison; and an entailment determination unit (23) that obtains a feature amount for each of the identified combinations, and determines whether the first text entails the second text based on the obtained feature amounts.

Abstract: A word classification system is provided with an inter-word pattern learning section for learning at least either the context information or the layout information between classification-known words which co-appear and creating an inter-word pattern for determining whether data relating to a word pair which is a combination of words is data relating to a same-classification word pair which is the combination of words in the same classification or data relating to a different-classification word pair which is a combination of words in different classifications on the basis of the relationship between the classification-known words which co-appear in a document.

Abstract: Sets of strings of which the drawing positions are arranged in one direction are extracted from a document as attribute groups. An attribute name score is calculated for each attribute group to determine an extent to which each attribute group is a set of attribute names. Based on the attribute name scores, an attribute name group is selected out of the attribute groups. From among the attribute groups, an attribute group which includes a string which is the same as at least one string of the attribute name group and of which the drawing position is the same as that of the string of the attribute name group is selected. From the string at the same drawing position, an attribute name is extracted. From the other strings of the selected attribute group than those at the same drawing position, an attribute value corresponding to the attribute name is extracted.

Abstract: A cooccurrence dictionary creating system includes: a language analyzing section which subjects a text to a morpheme analysis, a clause specification, and a modification relationship analysis between clauses, a cooccurrence relationship collecting section which collects cooccurrences of nouns in each clause of the text, modification relationships of nouns and declinable words, and modification relationships between declinable words as cooccurrence relationships, a cooccurrence score calculating section which calculates a cooccurrence score of the cooccurrence relationship based on a frequency of the collected cooccurrence relationship, and a cooccurrence dictionary storage section which stores a cooccurrence dictionary in which a correspondence between the calculated cooccurrence score and the cooccurrence relationship is described.

Abstract: A relationship information expansion apparatus capable of acquiring a new relationship based on a relationship information piece including two or more language expressions having a semantic relationship is provided. The relationship information expansion apparatus generates a candidate expanded relationship information piece in which at least one language expression included in the relationship information piece was replaced with a similar language expression, and acquires a score that indicates a probability that the candidate expanded relationship information piece has a semantic relationship. The relationship information expansion apparatus selects an expanded relationship information piece, which is a candidate expanded relationship information piece having a high score among candidate expanded relationship information pieces.

Abstract: An information classification device (1) is provided with an union of sets determination unit (10) which performs correct/incorrect determination regarding a content to be classified using a union of sets rule, and an individual determination unit (11) which applies a plurality of individual determination rules to the content to be classified which has been determined as correct, determines whether the content matches the condition, and performs correct/incorrect determination again regarding the content to be classified which has been determined as correct on the basis of the determination result of each individual determination rule. The union of sets determination rule is created using a result of correct/incorrect determination previously performed by two or more people with respect to a plurality of contents which are different from the contents to be classified, and also using feature amounts of respective different contents.

Abstract: The disclosed apparatus uses a training data generation apparatus 2, which generates training data used for creating characteristic expression extraction rules. The training data generation apparatus 2 includes: a training data candidate clustering unit 21, which clusters a plurality of training data candidates assigned labels indicating annotation classes based on feature values containing respective context information, and a training data generation unit 22 which, by referring to each cluster obtained using the clustering results, obtains the distribution of the labels of the training data candidates within the cluster, identifies training data candidates that meet a preset condition based on the obtained distribution, and generates training data using the identified training data candidates.

Abstract: An information analysis apparatus, an information analysis method, and a program are provided that enable target information to be determined in units of single sentences, rather than in units of plural sentences, while taking into consideration the tendency of appearance of the target information. An information analysis apparatus 5 is used to perform an analysis on text information to determine whether or not the text information corresponds to the target information.

Abstract: According to the present invention, phrases of the same kind can be extracted from a plurality of documents having various formats. A storage device stores a plurality of documents that have various formats. A pattern candidate creating unit receives a list of input words that are selected as samples among phrases that are to be included in a dictionary. The pattern candidate creating unit selects one document, determines forward and backward character strings of input words in the selected document as candidates of patterns, and stores the forward and backward character strings as a pattern candidate. The pattern candidate creating unit executes the above processes for each of the documents. A phrase candidate creating unit extracts phrases interposed between patterns included in the pattern candidate as candidates of phrases to be output, and stores the extracted phrases as a phrase candidate.

Abstract: A cooccurrence dictionary creating system includes: a language analyzing section which subjects a text to a morpheme analysis, a clause specification, and a modification relationship analysis between clauses, a cooccurrence relationship collecting section which collects cooccurrences of nouns in each clause of the text, modification relationships of nouns and declinable words, and modification relationships between declinable words as cooccurrence relationships, a cooccurrence score calculating section which calculates a cooccurrence score of the cooccurrence relationship based on a frequency of the collected cooccurrence relationship, and a cooccurrence dictionary storage section which stores a cooccurrence dictionary in which a correspondence between the calculated cooccurrence score and the cooccurrence relationship is described.

Abstract: A word classification system is provided with an inter-word pattern learning section for learning at least either the context information or the layout information between classification-known words which co-appear and creating an inter-word pattern for determining whether data relating to a word pair which is a combination of words is data relating to a same-classification word pair which is the combination of words in the same classification or data relating to a different-classification word pair which is a combination of words in different classifications on the basis of the relationship between the classification-known words which co-appear in a document.

Abstract: Sets of strings of which the drawing positions are arranged in one direction are extracted from a document as attribute groups. An attribute name score is calculated for each attribute group to determine an extent to which each attribute group is a set of attribute names. Based on the attribute name scores, an attribute name group is selected out of the attribute groups. From among the attribute groups, an attribute group which includes a string which is the same as at least one string of the attribute name group and of which the drawing position is the same as that of the string of the attribute name group is selected. From the string at the same drawing position, an attribute name is extracted. From the other strings of the selected attribute group than those at the same drawing position, an attribute value corresponding to the attribute name is extracted.

Abstract: An evaluation polarity of reputation information with an unknown evaluation polarity is estimated by utilizing reputation information with a known evaluation polarity. The present polarity estimation system is a polarity estimation system for estimating an evaluation polarity indicating whether reputation information is positive or negative, and includes a reputation information storage part that precedently stores reputation information with a known evaluation polarity; and a polarity estimating means for estimating an evaluation polarity of reputation information with an unknown evaluation polarity on the basis of the reputation information with the known evaluation polarity precedently stored in the reputation information storage part.

Abstract: An imaging device wherein a camera module is controlled based on a personality file for module (individual control data) which is retrieved from a camera module and is peculiar to the camera module and on a personality file for sensor (type-dependent control data) relating to the type of the camera module stored in a memory section (second memory) in advance.

Abstract: There is disclosed a camera module that is mounted into an information terminal device having an electric power supplying means and a first controlling means, so that the camera module receives a supply of electric power fed from the electric power supplying means and is activated in response to the start-up signal outputted by the first controlling means.

Abstract: An imaging device wherein a camera module is controlled based on a personality file for module (individual control data) which is retrieved from a camera module and is peculiar to the camera module and on a personality file for sensor (type-dependent control data) relating to the type of the camera module stored in a memory section (second memory) in advance.

Abstract: An image pick-up apparatus comprises: a camera body; an image pick-up element which converts optical images into electric signals; a controller which controls the image pick-up element. The controller can either read or write data between a first memory and the controller and also between a second memory and the controller via a first common bus, and the camera body is structured so that the first memory can be removed therefrom and attached thereto. The image pick-up apparatus further comprises a sensor which detects that the first memory has been removed from the camera body and then outputs a detected signal.

Abstract: An eletronic instrument includes: an analyzer that analyzes an image stored in an image storage device; a judging device that judges whether tag information corresponding to the image that is stored is appropriate or not, based on the results of analyses by the analyzer; a correction information forming device that forms correction information showing that the tag information has been corrected based on the results of analyses, when the tag information related with the image was judged not to be appropriate; and a tag information setting device that establishes the tag information by including the correction information.