A method for suggesting revisions to a document-under-analysis from a seed database, the seed database including a plurality of original texts each respectively associated with one of a plurality of final texts, the method for suggesting revisions including selecting a statement-under-analysis (“SUA”), selecting a first original text of the plurality of original texts, determining a first edit-type classification of the first original text with respect to its associated final text, generating a first similarity score for the first original text based on the first edit-type classification, the first similarity score representing a degree of similarity between the SUA and the first original text, selecting a second original text of the plurality of original texts, determining a second edit-type classification of the second original text with respect to its associated final text, generating a second similarity score for the second original text based on the second edit-type classification, the second similarity score representing a degree of similarity between the SUA and the second original text, selecting a candidate original text from one of the first original text and the second original text, and creating an edited SUA (“ESUA”) by modifying a copy of the first SUA consistent with a first candidate final text associated with the first candidate original text.

A method for suggesting revisions to a document-under-analysis from a seed database, the seed database including a plurality of original texts each respectively associated with one of a plurality of final texts, the method for suggesting revisions including selecting a statement-under-analysis (“SUA”), selecting a first original text of the plurality of original texts, determining a first edit-type classification of the first original text with respect to its associated final text, generating a first similarity score for the first original text based on the first edit-type classification, the first similarity score representing a degree of similarity between the SUA and the first original text, selecting a second original text of the plurality of original texts, determining a second edit-type classification of the second original text with respect to its associated final text, generating a second similarity score for the second original text based on the second edit-type classification, the second similarity score representing a degree of similarity between the SUA and the second original text, selecting a candidate original text from one of the first original text and the second original text, and creating an edited SUA (“ESUA”) by modifying a copy of the first SUA consistent with a first candidate final text associated with the first candidate original text.

A text containing a word is received by a computing device. The word is compared to inventory words in a sense inventory. The sense inventory comprises at least one inventory word and at least one concept corresponding to the at least one inventory word. Upon matching the word to an inventory word in the sense inventory, a concept for the word is identified by comparing each concept related to the inventory word to the word. The concept is assigned the word.

A multilingual tag-based review system where users from around the world, can browse and submit review over the Internet, for product purchases or other reviews related to the user's interests. The system has a server with a database. The database has authorized, pre-written tags and stored ratings associated with the product or the items being reviewed, and displays the tags and ratings on the website with the product or item being reviewed. Users can quickly gauge the ratings in their own language to determine their interest in the item or whether or not to purchase the product by browsing the reviews or leaving a review of the product, if the user has purchased the product, or item of interest.

A translation corpus creation method of the present disclosure includes generating plural paraphrasing candidate sentences for a first original sentence in a first language by paraphrasing one or plural fragments among plural fragments included in the first original sentence into other expressions in the first language by a paraphrasing candidate sentence generation unit, identifying one or plural paraphrasing candidate sentences in the same meaning as the meaning of the first original sentence from the plural paraphrasing candidate sentences as one or plural paraphrasing sentences by a paraphrasing sentence identification unit, and generating a new set of sentences by setting the one or plural identified paraphrasing sentences and a second original sentence translated from the first original sentence as a set of sentences to create a translation corpus with the generated and new set of sentences by a translation corpus creation unit.

A paraphrase generation method according to the present disclosure generates one or more paraphrases of an original text by paraphrasing, within an acceptable limit for accepting paraphrasing, one or more of a plurality of fragments included in the original text into another expression in the language of the original text, the plurality of fragments being obtained by dividing the original text in accordance with a predetermined rule.

Provided is a method of managing a server having stored thereon a phrase table containing phrase pairs each being a pair of a phrase in a first language and a phrase in a second language different from the first language. In the method, a processor receives combinations of the phrase pairs used to generate respective candidate target texts which are generated by translation of a source text in the first language into a target text in the second language as candidates for the target text in the second language, and records combination information (for example, a data structure and paths) in the server, the combination information identifying, in the phrase pairs contained in the phrase table, the combinations of the phrase pairs used to generate the respective candidate target texts.

Provided is an information processing apparatus including a first reception unit that receives modification to a translation result of at least one first document from a user, a generation unit that generates a translation rule corresponding to the modification received by the first reception unit, a second reception unit that receives original texts of at least one second document, and a utilization unit that utilizes the translation rule generated by the generation unit at the time of translating the original texts received by the second reception unit, depending on relevance between the at least one first document and the second document.

According to one embodiment, a display assist apparatus includes an acquisition unit, a first processor, a second processor, and a display controller. The acquisition unit acquires a character string. The first processor divides the character string into first segments each of which is a segment representing a semantic cluster and generates a plurality of divided character strings. The second processor detects, for the character string, second segments each of which is a segment larger than the each of the first segments. The display controller performs display control to make a distinction between the first segments and the second segments when displaying the plurality of divided character strings.

A method for translating a text written or otherwise communicated in a source natural language into a text written or otherwise communicable in target natural language, in reliance upon a multidimensional model, relies on determining the core concept in the sentences of the source text, and leverages the determined core concepts to create the target language translation. The method includes processing the source natural language text into sentences, then parsing the sentences, including assigning codes and/or directional operators to realize parsed sentences according to the model. The sentence models are then processed effect the actual translation to the target natural language text, and communicated.