Fujitsu Corporation

Tomoki Nagase

Masaru Fuji

Seiji Okura

Yuchang Cheng

Akira Ushioda

Masataka Kadotani

Nobuyuki Katae

A parallel-translation dictionary creating apparatus that includes a processor configured to create a parallel-translation dictionary; the processor extracts words from each of the plurality of documents; performs an estimation and storage of a semantic classification of the extracted words; based on a result of the estimation of the semantic classification for the word in the document that is a current processing target and the word pair registered in the parallel-translation word list; updates, to the semantic classification of the word for which the semantic classification has been estimated, the semantic classification of a corresponding word that corresponds to the word and to the subject matter of the document that is the current processing target; and creates the parallel-translation dictionary based on the semantic classification of the word obtained by the estimation of the semantic classification of the word and the update of the semantic classification of the corresponding word.

Parallel-translation dictionary creating apparatus and method

An information processing method executed by an information processing apparatus, includes receiving a keyword; extracting one or more experts related to a document including the keyword from document information, the document information including a plurality of documents registered within a period of time including a plurality of periods and information on an expert related to each of the plurality of documents; determining a score in each period based on a ratio of a number of registered documents related to the keyword to a number of all registered documents and a coefficient increased in value as the period becomes newer, with respect to each of the one or more experts; determining an expert value related to the keyword for each of the one or more experts by adding together the score in each period; and ranking each of the one or more experts based on comparison of the expert value.

Information processing method, information processing apparatus and storage medium to determine ranking of registrants

A machine translation apparatus configured to translate an input sentence and output a translated sentence in a target language, the machine translation apparatus includes a rule acquirer configured to acquire a difference between an input example sentence and a replaced example sentence which is obtained by replacing the input example sentence, and acquire a replacement rule based on the difference and each of meaning representations which indicate each relationship of words in the input example sentence and the replaced example sentence; and a translator configured to apply the replacement rule acquired by the rule acquirer to the input sentence and output the translated sentence based on the meaning representations and a meaning representation indicating of relationship of words in the input sentence.

Machine translation apparatus, translation method, and translation system

A machine translation device that translates a first language sentence into a second language sentence, the machine translation device includes: a translation unit configured to translate the first language sentence or the second language sentence into a third language sentence; and a second language translated sentence output unit configured to output a second language sentence corresponding to the first language sentence using a search result obtained by searching a database that stores more example sentences of a third language than example sentences of a first language and a second language using the translated third language sentence as a search key.

Machine translation device, machine translation method, and recording medium storing machine translation program

A Japanese proofreading apparatus has a correction history corpus, a proofreading candidate generation unit, a proofreading availability determination unit, and an automatic proofreading unit. The correction history corpus stores negative sentences as post-proofreading sentences and positive example sentences as post-proofreading sentences, in association with each other. The proofreading candidate generation unit acquires the post-proofreading sentences corresponding to the pre-proofreading sentences from the correction history corpus, according to characteristics of a proofreading target sentence. The proofreading availability determination unit selects, from the post-proofreading sentences acquired by the proofreading candidate generation unit, post-proofreading sentences with degrees of similarity between the proofreading target sentence and the post-proofreading sentences equal to or more than a predetermined threshold value, as proofreading candidates. The automatic proofreading unit proofreads the proofreading target sentence, using, out of the post-proofreading sentences selected by the proofreading availability determination unit, a post-proofreading sentence with the highest degree of similarity.

Text proofreading apparatus and text proofreading method using post-proofreading sentence with highest degree of similarity

A typical sentence having a specific typical characteristic in the sentence is divided. A division target typical sentence is divided on the basis of a small clause definition. The sentence is divided where positions suitable for dividing the typical sentence based on the structure are expressed by a user. A small clause string including small clauses that serve as independent sentences is created after the division. The small clause string is compared to the structure patterns, and a structure pattern that is determined to match the small clause string is selected as a result of the typical sentence division.

Computer-readable medium having sentence dividing program stored thereon, sentence dividing apparatus, and sentence dividing method

A retrieval result outputting apparatus evaluates degrees of matching on a character block basis between an input example sentence serving as a retrieval condition and retrieval example sentences retrieved using the input example sentence as the retrieval condition; extracts one of the retrieval example sentences as an extraction example sentence in accordance with the evaluation; selects a portion of the input example sentence as a reevaluation portion with reference to the extraction example. And then reevaluates on degrees of matching a character block basis between the retrieval example sentences and the reevaluation portion; re-extracts one of the retrieval example sentences as a re-extracted example sentence in accordance with the reevaluation; and outputs the extracted and re-extracted example sentences.

Retrieval result outputting apparatus and retrieval result outputting method

A device includes a parsing unit that parses an input sentence into a plurality of clauses, an identification unit that identifies, as a target area, based on the clauses resulting from the parsing, any of the clauses corresponding to an area specified, a setting unit that sets, as a target clause, any of the clauses located at a boundary of the target area identified, and sets, as a candidate for modification of the target clause, any of the clauses adjacent to the target clause in the target area. A judgment unit judges whether there exists a relationship of modification between the target clause and the candidate for modification and a determination unit determines, when the judgment unit judges that there is the relationship of modification, a translation area based on the target area, the target clause, and the candidate for modification.

Translation assistance device and method

In a computer for supporting translation work, an acquisition unit retrieves a pair of original document including a plurality of original sentences and translated document including a plurality of translated sentences from a document storage unit. An estimation unit counts the number of original sentences included in the original document and the number of translated sentences included in the translated document, and estimates a position of a translated sentence corresponding to each original sentence in the translated document based on a ratio of the number of original sentences to the number of translated sentences and a positional order of each original sentence in the original document. An alignment unit aligns each original sentence with the translated sentence located at the estimated position, and outputs information indicating the correspondences between the original and translated sentences.

Translation supporting program, apparatus, and method

A translation memory system enabling the user to not only narrow down the view range of search result, but also view a surrounding context of a retrieved text. Stored parallel texts include sentence-class and segment-class parallel texts. Parallel texts relevant to a given input text are retrieved and subjected to calculation of match rates with respect to the input text. A downward link is then added to each retrieved sentence-class parallel text, while an upward link is added to each retrieved segment-class parallel text. A search result screen shows a best matching parallel text with an expand button and/or a shrink button. The expand button causes the current parallel text to be replaced with an upper-class parallel text pointed at by a corresponding upward link. The shrink button causes the current parallel text to be replaced with a lower-class parallel text pointed at by a corresponding downward link.

Computer program, apparatus, and method for searching translation memory and displaying search result

A subject-of-analysis input section inputs an input sentence or phrase to be analyzed. A dictionary unit holds dictionary data for dictionary consultation for a language of the input sentence. A morphemic analyzer consults the dictionary for the input sentence and recognizes breaks between every input word. A grammatical rule unit holds grammatical rules for parsing in the form of a general context-free grammar. A parsing unit applies the grammatical rules to the input sentence for parsing of the sentence. An analysis table unit stores the analysis intermediate results by the parsing unit in predetermined storage locations and holds an analysis table for storing the storage locations for the intermediate analysis results and/or pointers to the storage locations. The intermediate analysis result information in the analysis table unit includes syntactic category information and at least one of syntactic, semantic and control attributes.

Growing community of inventors

Kawasaki, Japan

Tomoki Nagase