Abstract: An information processing device includes a morphological-analysis performing unit that performs morphological analysis on character strings to identify the word classes of words included in the character strings; a specifying unit that specifies a permutation of target terms, which are words selected from the character strings, on the basis of the identified word classes; and a generating unit that calculates permutation pointwise mutual information, which is pointwise mutual information of the permutation in a corpus, and learns the permutation and the permutation pointwise mutual information, to generate a permutation pointwise-mutual-information model, which is a trained model.

Abstract: A sentence structure vectorization device includes processing circuitry to generate a plurality of morphemes by performing morphological analysis on an input sentence; to generate a dependence structure graph regarding the plurality of morphemes by performing dependency parsing on the plurality of morphemes; and to generate a sentence structure vector by extracting a plurality of pieces of partial structure information from the dependence structure graph and converting a morpheme string corresponding to the plurality of pieces of partial structure information into a numerical sequence.

Abstract: An information processing device includes an acquisition unit that acquires a plurality of character strings, a morphological analysis execution unit that executes morphological analysis on the plurality of character strings, and a generation unit that generates a learned model for inferring meaning of a first word included in a plurality of words among a plurality of speech-parted words obtained by executing the morphological analysis on the plurality of character strings based on a plurality of words as a plurality of predicates among the plurality of speech-parted words and a plurality of words among the plurality of speech-parted words.

Abstract: A learning data generation device includes processing circuitry to extract a cause expression and a result expression from an input text, and to generate a modified text by at least one of a method of interchanging the cause expression and the result expression and a method of specifying one of the cause expression and the result expression as a modification target sentence and replacing the modification target sentence with a replacement candidate sentence dissimilar to the modification target sentence.

Abstract: A similar expression collecting unit (103) collects a word/phrase of an expression similar to an analysis viewpoint word/phrase and a word embedding corresponding the word/phrase from distributed representations of words data. A dimension selecting unit (104) selects a dimension of a word embedding depending on the analysis viewpoint word/phrase, and compresses a word embedding corresponding to the word/phrase collected by the similar expression collecting unit (103) in the selected dimension.

Abstract: A sentence structure vectorization device includes processing circuitry to generate a plurality of morphemes by performing morphological analysis on an input sentence; to generate a dependence structure graph regarding the plurality of morphemes by performing dependency parsing on the plurality of morphemes; and to generate a sentence structure vector by extracting a plurality of pieces of partial structure information from the dependence structure graph and converting a morpheme string corresponding to the plurality of pieces of partial structure information into a numerical sequence.

Abstract: A language model generating device according to the present invention includes: a paraphrase generating unit to generate, by using morphemes of a phrase included in learning example sentences that include a plurality of sentences and using synonyms for original expressions of the morphemes, a plurality of paraphrases that include a combination of an original expression of a morpheme and a synonym for an original expression of a morpheme and a combination of synonyms for original expressions of morphemes; and a language model generating unit to generate a language model that is based on an n-gram model from the plurality of paraphrases generated and the learning example sentences.

Abstract: A similar expression collecting unit (103) collects a word/phrase of an expression similar to an analysis viewpoint word/phrase and a word embedding corresponding the word/phrase from distributed representations of words data. A dimension selecting unit (104) selects a dimension of a word embedding depending on the analysis viewpoint word/phrase, and compresses a word embedding corresponding to the word/phrase collected by the similar expression collecting unit (103) in the selected dimension.

Abstract: A language model generating device according to the present invention includes: a paraphrase generating unit to generate, by using morphemes of a phrase included in learning example sentences that include a plurality of sentences and using synonyms for original expressions of the morphemes, a plurality of paraphrases that include a combination of an original expression of a morpheme and a synonym for an original expression of a morpheme and a combination of synonyms for original expressions of morphemes; and a language model generating unit to generate a language model that is based on an n-gram model from the plurality of paraphrases generated and the learning example sentences.