Abstract: A text processing system that is able to appropriately determine textual entailment between sentences with high coverage is provided. The text processing system is configured to execute: processing of extracting a common substructure that is a partial structure of a same type, the partial structure being common to a first sentence and a second sentence and, based on the a structure representing the first sentence and a structure representing the second sentence; processing of extracting at least one of a feature amount representing a dependency relationship between the at least one common substructure in the first and second sentences and a feature amount representing a dependency relationship between the common substructure in the first and second sentences and a substructure different from the common substructure; and processing of determining an entailment relationship between the first sentence and the second sentence by using the extracted feature amount.

Abstract: A similar sentence set generation unit 81 groups sentences representing a same concept or event from a set of analysis target sentences, to generate a similar sentence set. A similar sentence set extraction unit 82 extracts, using one or more specific sentence extractors each capable of extracting a specific sentence belonging to a specific classification from the set of analysis target sentences, one or more sentences not extracted by any of the specific sentence extractors from among the sentences belonging to the similar sentence set, as an exclusion similar sentence set.

Abstract: Provided is a text processing system which, when an attribute corresponding to one tabulation axis is set, is capable of generating a text group which will produce non-obvious tabulation results when cross-tabulation is performed using that attribute. At the time of input of respective attribute values of an attribute which corresponds to a tabulation axis in cross tabulation and a document associated with any one of the attribute values of the attribute, text extraction means 71 extracts portion not including the attribute value of the attribute from each text obtained by dividing the document into predetermined units. Group generation means 72 performs entailment recognition between texts on the extracted texts and groups texts having an entailment relation.

Abstract: Provided is a text processing system capable of classifying a plurality of texts into groups whose overviews are able to be grasped and classifying texts semantically having entailment relation into the same group even if the texts are not determined to have the entailment relation. Entailment recognition means 71 performs entailment recognition between texts on given texts. Group generation means 72 selects an individual text and generates a group including texts entailing the selected text as members. Group integration means 73 integrates groups in the case where groups satisfy a predetermined condition based on the degree of overlap of members between groups.

Abstract: An entailment evaluation device includes: a generation unit which generates first information indicating at least the order of occurrence of events of first and second simple sentences included in the hypothesis text and generates second information indicating at least the order of occurrence of events of third and fourth simple sentences included in a target text, the third simple sentence being related to the first simple sentence, the fourth simple sentence being related to the second simple sentence; a calculation unit which obtains a calculation result by comparing, based on the first and second information, the order of occurrence of events of first and second simple sentences and order of occurrence of events of third and fourth simple sentences; and a determination unit which determines, based on at least the calculation result, whether or not the target text entails the hypothesis text.

Abstract: A synonym relation determination device comprises: a synonym expression candidate storage unit which associates and stores a synonym candidate (EW) with the synonym source (OW); a text gathering unit which associates and gathers text with an issuing time; a synonym candidate search unit which calculates from the issuing time of the text a time interval (PD) in which the synonym candidate is searched in a text set (TX); a synonym source search unit which searches for a synonym source from the text set of a period which overlaps with the time interval in which the synonym candidate is searched for and calculates an occurrence of the synonym source; and synonym relation extraction unit which, when the occurrence of the synonym source is present in the time interval in which the synonym candidate is searched for, extracts a synonym relation between the synonym candidate and the synonym source.

Abstract: A classification dictionary generation apparatus includes: a lower threshold storage unit that stores lower threshold information that determines a lower threshold of dimensional values of a classification dictionary for classifying a category of a document; and a control unit that generates the classification dictionary based on learning data whose category is known, wherein the control unit generates, based on the lower threshold information stored in the lower threshold storage unit, the classification dictionary in which all of the dimensional values are equal to or larger than the lower threshold.

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 entailment evaluation device includes: a generation unit which generates first information indicating at least the order of occurrence of events of first and second simple sentences included in the hypothesis text and generates second information indicating at least the order of occurrence of events of third and fourth simple sentences included in a target text, the third simple sentence being related to the first simple sentence, the fourth simple sentence being related to the second simple sentence; a calculation unit which obtains a calculation result by comparing, based on the first and second information, the order of occurrence of events of first and second simple sentences and order of occurrence of events of third and fourth simple sentences; and a determination unit which determines, based on at least the calculation result, whether or not the target text entails the hypothesis text.

Abstract: A similar data search device includes: an inverted index generating unit which determines size ranges of sets of search targets for each of inverted indexes so that the number of sets of search targets is not smaller than a specified number and generates inverted indexes by dividing the sets of search targets according to the determined size ranges; an unnecessary inverted index identifying unit which determines, based on a size of a set of search conditions and a threshold value specified for a similarity between sets, a condition necessary for the similarity to be no smaller than the threshold value, and identifies, as an inverted index unnecessary for searches, any inverted index other than those inverted indexes containing a set whose minimum size value satisfies the condition; and a data search unit which conducts a search on a non-identified inverted index.

Abstract: A text mining device includes: an analysis unit which acquires, from data including text and one or more attributes including an attribute name and an attribute value and associated with the text, the attributes as analysis viewpoints, analyzes the data using the respective analysis viewpoints to obtain an analysis result from each analysis viewpoint, and generates result vectors of the respective analysis viewpoints; a similarity acquisition unit which acquires a vector similarity between the result vectors of the plural analysis viewpoints; and a recommendation unit which extracts and output a combination of the analysis viewpoints as a recommendation candidate on basis of the vector similarity.

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 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 purpose of the present invention is to generate a dictionary for monitoring text information such that it is possible to achieve high-precision detection compared to conventional art. A feature degree calculation unit 3 compares the statistics of a positive example group and a negative example group, and calculates the degree by which a phase of interest appears in the positive example group as the feature degree. A usefulness degree calculation unit 21 calculates a usefulness degree by using the length of the phrase, the frequency at which the phrase appears within the positive example group, and an index pertaining to an inclusion relationship between phrases for each phrase extracted by means of a phrase extraction unit 1.

Abstract: A text mining device (2) is used in which data composed of a set of records including an attribute value and text data is used as analysis target data. The text mining device (2) includes an analysis perspective candidate generation unit (20) that extracts an attribute value from the analysis target data and generates an analysis perspective candidate using the extracted attribute value, and a characteristic degree calculation unit (21) that compares text data in a record including the attribute value extracted as the analysis perspective candidate with text data in a record set that includes at least a record other than the record including the attribute value in the analysis target data, and calculates a characteristic degree indicating a relationship between the analysis perspective candidate and the analysis target data based on a result of the comparison.

Abstract: The present invention is a text mining system comprising a synonym cluster acquiring section configured to acquire synonym clusters from texts in text data to be analyzed, the synonym clusters each being a collection of synonymous texts, an implication relationship acquiring section configured to acquire implication relationships among the synonym clusters, and an implication graph generating section configured to generate an implication graph including vertices of synonym clusters and directed edges each indicating a direction from an implied synonym cluster to an implying synonym cluster from the implication relationships among the synonym clusters.

Abstract: A synonym relation determination device comprises: a synonym expression candidate storage unit which associates and stores a synonym candidate (EW) with the synonym source (OW); a text gathering unit which associates and gathers text with an issuing time; a synonym candidate search unit which calculates from the issuing time of the text a time interval (PD) in which the synonym candidate is searched in a text set (TX); a synonym source search unit which searches for a synonym source from the text set of a period which overlaps with the time interval in which the synonym candidate is searched for and calculates an occurrence of the synonym source; and synonym relation extraction unit which, when the occurrence of the synonym source is present in the time interval in which the synonym candidate is searched for, extracts a synonym relation between the synonym candidate and the synonym source.

Abstract: A term synonym acquisition apparatus includes: a first generating unit which generates a context vector of an input term in an original language and a context vector of each synonym candidate in the original language; a second generating unit which generates a context vector of an auxiliary term in an auxiliary language that is different from the original language, where the auxiliary term specifies a sense of the input term; a combining unit which generates a combined context vector based on the context vector of the input term and the context vector of the auxiliary term; and a ranking unit which compares the combined context vector with the context vector of each synonym candidate to generate ranked synonym candidates in the original language.

Abstract: A term translation acquisition apparatus includes: a creation unit which creates a statistical model based on a set of input terms' context vectors, wherein the set of terms including at least two terms, are in the same source language and describe the same concept; and a ranking unit which uses the created statistical model to score terms in a target language that are considered as translation candidates for the concept.

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.