Abstract: To provide an implication determining device, an implication determining method, and an implication determining program capable of improving implication determination performance. A new fact determination unit determines whether a given hypothesis is a new fact that indicates a first revealed fact in a hypothesis implied sentence that is a sentence implying the given hypothesis based on a specific expression written in the hypothesis implied sentence. An implication determination unit determines whether the given hypothesis is implied in a sentence to be determined that is a sentence to be determined whether the hypothesis is included.

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 synonymous expression assessment device includes: synonymy assessment means for receiving input of binary relations each of which includes a nominal and a predicate, and assessing whether or not the input binary relations are synonymous using a similarity between input nominals and a similarity between input predicates; and inter-predicate similarity computation means for, when computing the similarity between the input predicates based on a distribution of occurrence frequencies of nominals that are in binary relations to the input predicate in a document set, performing the computation using a distribution of only nominals that are used in the same type of concept as the input nominal.

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: A conversation-sentence generation device according to the invention of this application includes: an input unit that receives, as input information, a conversation sentence given from a user to an agent, and clue information based on which a physical and psychological state of the agent is estimated; an agent state storing unit that stores the physical and psychological state of the agent as an agent state; an agent state estimating unit that estimates a new agent state based on the input information and the agent state; an utterance intention generating unit that generates, based on the input information and the agent state, an utterance intention directed from the agent to the user; a conversation sentence generating unit that generates, based on the input information, the agent state, and the utterance intention, a conversation sentence given from the agent to the user; and an output unit that outputs the conversation sentence generated by the conversation sentence generating unit.

Abstract: Disclosed are a text mining method, device, and program capable of performing text mining with a specific topic as an object with high precision. An element identification unit calculates a feature degree, which is an index for indicating a degree that within a text set of interest, which is a set of text that is to be analyzed, an element of the text appears. An output unit identifies distinctive elements within the text set of interest on the basis of the calculated feature degree and outputs the identified elements. The element identification unit corrects the feature degree on the basis of a topic relatedness degree, which is a value indicating a degree related to a topic of analysis, which is a topic for which each text portion of the text being analyzed has been partitioned into predetermined units that are to be analyzed.

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 question-answering device, a question-answering method, and a question-answering program that can obtain an answer to an inputted query with high probability are described. A score calculation element 305 determines a matching degree between the group of the style and the topic of an inputted query and the group of the style and the topic of the query of question-answer pairs. A search result presentation element 306 narrows the question-answer pairs on the basis of the matching degree.

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: A synonymous expression assessment device includes: synonymy assessment means for receiving input of binary relations each of which includes a nominal and a predicate, and assessing whether or not the input binary relations are synonymous using a similarity between input nominals and a similarity between input predicates; and inter-predicate similarity computation means for, when computing the similarity between the input predicates based on a distribution of occurrence frequencies of nominals that are in binary relations to the input predicate in a document set, performing the computation using a distribution of only nominals that are used in the same type of concept as the input nominal.

Abstract: A text processing apparatus is provided with a segment determination unit 36 and a descriptive content determination unit 33. The segment determination unit 36 determines, with respect to a homogeneous segment that is similar to segments constituting a first text which is set as an analysis target (analysis target text) and that is included in another first text, whether the content thereof is included in a second text. The descriptive content determination unit 33 determines whether each segment constituting the analysis target text should be described in a corresponding second text, based on the determination result.

Abstract: A text mining system including an analysis target search unit which judges whether a commonality in expressions among text data exists, an analysis viewpoint generation unit which generates an analysis viewpoint to extract an expression from the target data, a positive example set identification unit which identifies a positive example set including an expression matching the generated analysis viewpoint in the target data, a characteristic quantity calculation unit which calculates a characteristic quantity showing a degree of characterizing the positive example set of expressions in the target data, and a characteristic expression ranking unit which extracts expressions having the calculated characteristic quantity equal to or greater than a predetermined threshold as characteristic expressions and ranks the extracted characteristic expressions, and the target search unit extracts the analysis viewpoint among which a difference in ranks provided for the characteristic expressions is equal to or greater than

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 text mining apparatus, a text mining method, and a program are provided that accurately discriminate inherent portions of each of a plurality of text data pieces including a text data piece generated by computer processing. A text mining apparatus 1 to be used performs text mining using, as targets, a plurality of text data pieces including a text data piece generated by computer processing. Confidence is set for each of the text data pieces. The text mining apparatus 1 includes an inherent portion extraction unit 6 that extracts an inherent portion of each text data piece relative to another of the text data pieces, using the confidence set for each of the text data pieces.