Fujitsu Corporation

Seiji Okura

Masahiro Kataoka

Akira Ushioda

Masao Ideuchi

Masaru Fuji

Tomoki Nagase

Tatsuo Yamashita

Shigeki Fukuta

Kensuke Baba

Tomoya Noro

Akira Nakagawa

Jun Takahashi

Shinji Kikuchi

Koji Tsukamoto

Takao Mohri

Akinori Taguchi

Kentaro Murase

Takuya Kamimura

Toshiyuki Fukuoka

Satoshi Onoue

Fumiaki Nakamura

Junya Saito

An extraction method executed by a computer includes: acquiring a first word input by a first user; acquiring a second word input by a second user; calculating a first distributed representation of a first character string, the first character string including the first word and a character string that identifies the first user; calculating a second distributed representation of a second character string, the second character string including the second word and a character string that identifies the second user; calculating a similarity between the first distributed representation and the second distributed representation; and extracting a word associated with the second distributed representation on a basis of the similarity.

Extraction method, computer-readable recording medium storing extraction program, and information processing device

An apparatus generates an index including positions of morphemes included in a target text data and semantic attributes between the morphemes corresponding to the positions. The apparatus gives information including positions of morphemes included in an input query and semantic attributes between the morphemes corresponding to the positions to the query, and executes a retrieval on the target text data, based on the information given to the query and the index.

Effective retrieval of text data based on semantic attributes between morphemes

A memory stores therein a document and a plurality of word vectors that are word embeddings respectively computed for a plurality of words. A processor extracts, with respect to one of the words, two or more surrounding words within a prescribed range from one occurrence position where the one word occurs, from the document, and computes a sum vector by adding word vectors corresponding to the surrounding words. The processor determines a parameter such as to predict the surrounding words from the sum vector and the parameter using a machine learning model. The processor stores the parameter as context information for the one occurrence position, in association with the word vector corresponding to the one word.

Method and apparatus for generating context information

An index generation method includes: executing an extraction process that includes extracting a plurality of morphemes from document information; and executing a generation process that includes generating index information with respect to each of the plurality of morphemes, wherein the index information includes a first logical value and a second logical value, wherein the first logical value indicates existence of a first morpheme associated with 'morpheme information indicating the first morpheme' and 'position information indicating a position of the first morpheme in the document information', and wherein the second logical value indicates existence of the first morpheme associated with &#x2018;attribute information indicating a semantic attribute of the first morpheme&#x2019; and &#x2018;position information indicating the position of the first morpheme&#x2019;.

Index generation method, data retrieval method, apparatus of index generation

A non-transitory computer-readable recording medium stores a semantic structure search program. The semantic structure search program causes a computer to execute the following process. The computer generates a plurality of search semantic symbols from a search request. Next, the computer specifies a position of a specific word that corresponds to the search request in a search target document, by the plurality of search semantic symbols and document semantic structure position information. The document semantic structure position information includes a relationship information between a plurality of semantic symbols and a plurality of positions of a plurality of words in the search target document. The plurality of semantic symbols represent a semantic structure corresponding to the plurality of words. Thereafter, the computer outputs a search result including the specific word and the position of the specific word in the search target document.

Semantic structure search device and semantic structure search method

A computer generates a plurality of encoded sentences in the first language by encoding a plurality of sentences in the first language in prescribed units. Next, the computer generates a plurality of encoded sentences in the second language by encoding a plurality of sentences in the second language, each of which is associated with each of the plurality of sentences in the first language, in the prescribed units. The computer generates alignment information based on a code included in each of the plurality of encoded sentences in the first language and a code included in an encoded sentence in the second language, which is associated with each of the plurality of encoded sentences in the first language. The alignment information indicates an alignment between a plurality of codes in the first language and a plurality of codes in the second language.

Alignment generation device and alignment generation method

A reservation managing method implemented by a computer, the reservation managing method includes: executing first processing in response to receiving of a condition for searching for a resource, the received condition being a condition specified from a user, the first processing including searching for a resource matching the received condition among a plurality of resources; storing information about transition of the condition for searching for a resource in a memory in association with the user based on a condition when a reservation by the user is not set among the received conditions; and outputting a notification that a reservation for one resource of the plurality of resources may be set to the user when a reservation for the one resource is canceled, and when the one resource matches the condition identified from the information stored in the memory in association with the user.

Reservation managing method, and information processing device, and non-transitory computer-readable storage medium for storing reservation managing program

An information processing device receives a specification of a word, and specifies an appearance position associated with the specified word by referring to information in which appearance positions in text data of respective words included in the text data are associated with each of the words. The information processing device specifies an attribute associated with the specified appearance position by referring to information in which attributes at respective appearance positions in the text data of respective words included in the text data are associated with the appearance positions.

Non-transitory computer readable recording medium, identification method, generation method, and information processing device

An apparatus receives, via an input device, query input data including a word or a phrase, and acquires search result set data using the query input data. The apparatus acquires, for a value indicating a strength of a relationship between each impression word included in an impression word group and each word included in the query input data, and extracts the first feature word group according to the value indicating the strength of the relationship with each word, from the impression word group. The apparatus displays the search result set data using the first feature word group as an item.

Search method and search device

A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process including generating index information regarding a first string data including a plurality of words or phrases, the index information indicating appearance positions of each of characters, setting flag information to the index information, the flag information indicating head positions plurality of words or phrases and end positions of each of the plurality of words or phrases, and extracting, from a second string data, a plurality of dividable words or phrases corresponding to the plurality of words or phrases by using the index information to which the flag information is set.

Non-transitory computer-readable storage medium, analysis method, and analysis device

A computer generates semantic structure information from a document. The semantic structure information includes a plurality of semantic structures in a plurality of sentences in the document and a plurality of morphemes included in each of the plurality of sentences belong to a corresponding semantic structure. The computer generates a plurality of codes by encoding the plurality of morphemes for each of the plurality of sentences. The computer specifies a specific code that corresponds to a specific morpheme from among the plurality of morphemes included in each of the plurality of sentences, wherein at least one morpheme is potentially missing in a semantic structure that the specific morpheme belongs to. A missing-portion information indicates the missing morpheme is included in a prior sentence in the document. The computer adds missing-portion information to the specific code for each of the plurality of sentences.

Search apparatus, encoding method, and search method based on morpheme position in a target document

A computer generates searching context information relating to appearance frequencies of words or semantic codes in a searching query sentence from the searching query sentence. Semantic analysis is performed on sentences included in documents so as to generate semantic structures, and each of the semantic structures includes three or more semantic codes and a relationship type among the semantic codes. A plurality of context information is generated and each context information relates to an appearance frequency of a word or a semantic code in a group of documents that match each of the semantic structures. The computer specifies one semantic structure of the semantic structures in accordance with the searching context information and the plurality of context information, and searches for a similar document by using the specified semantic structure.

Search apparatus and search method

A recording medium having stored therein an encoding program that causes a computer to execute a process, the process including first generating a plurality of word codes by assigning a compression code to each of a plurality of words contained in a sentence in a compression target document, second generating a plurality of pieces of semantic structure information respectively corresponding to the plurality of words by performing a semantic analysis of the sentence, third generating a plurality of semantic structure codes by assigning each of the plurality of compression codes to corresponding semantic structure information, and outputting the plurality of word codes and the plurality of semantic structure codes with a specific order.

Encoding device, encoding method and search method

A computer generates a plurality of pieces of syntax information respectively corresponding to a plurality of words in a compression target document by analyzing relationships between the plurality of words. Next, the computer assigns a plurality of compression codes to the plurality of words and to the plurality of pieces of syntax information. Then, the computer outputs the plurality of compression codes with an arrangement of a specific order.

Encoding apparatus, encoding method and search method

A processor performs semantic analysis on a query and generates one or more semantic structures where each structure is expressed by a graph. The processor generates retrieval keys corresponding to combinations of nodes connected directly or indirectly in the semantic structures, in addition to retrieval keys corresponding to minimum units of semantic connections between nodes in the generated semantic structures. The processor retrieves relevant documents whose sentences are matched to combinations of nodes, by using the generated retrieval keys, in the semantic structures stored in an index for retrieval on a database storing the documents.

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Meguro, Japan

Seiji Okura