494 results about "Synonym" patented technology

A method is applied to search terms for determining synonyms or other replacement terms used in an information retrieval system. User queries are first sorted by user identity and session. For each user query, a plurality of pseudo-queries is determined, each pseudo-query derived from a user query by replacing a phrase of the user query with a token. For each phrase, at least one candidate synonym is determined. The candidate synonym is a term that was used within a user query in place of the phrase, and in the context of a pseudo-query. The strength or quality of candidate synonyms is evaluated. Validated synonyms may be either suggested to the user or automatically added to user search strings.

Methods, systems, and apparatus, including computer program products, for identifying candidate synonyms of transliterated terms for query expansion. In one aspect, a method includes identifying multiple transliterated terms in a target language. For each transliterated term of the multiple transliterated terms in the target language, the transliterated term is mapped to one or more terms in a source language. For a first transliterated term of the multiple transliterated terms in the target language, one or more second transliterated terms of the multiple transliterated terms in the target language are identified as candidate synonyms of the first transliterated term, where each of the one or more second transliterated terms is mapped to at least one term in the source language that is also mapped from the first transliterated term.

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.

An operation determination processing section of a center extracts words included in the utterance of a driver and an operator, reads an attribute associated with each word from a synonym and related word in which an attribute is stored so as to be associated with each word, reads a domain of a candidate or the like for the task associated with the attribute from the synonym and related word in which domains of a candidate for a task associated with the read attribute or domains of a task to be actually performed are stored, totals the domains read for each word for words included in the utterance of the driver or the like, and estimates those related to a domain with a highest total score as the candidate for the task and the task to be actually performed. In this manner, it is possible to estimate the task with high accuracy.

The invention provides a system and a method of searching for information in a database using a query. In the method, it comprises the steps of: disambiguating the query to identify keyword senses associated with the query; disambiguating information in the database according to the keyword senses; indexing the information in the database according to the keyword senses; expanding the keyword senses to include relevant semantic synonyms for the keyword senses to create a list of expanded keyword senses; searching the database to find relevant information for the query using the expanded keyword senses; and providing search results of the included information containing the keyword senses and other semantically related words senses. The system comprises modules which disambiguate queries and information and indexes the information in a database of word senses.

Acronym and synonym pairs can be identified and retrieved automatically in a corpus and/or across an enterprise based on customer settings globally or for a single instance. Possible acronym and synonym term pairs can be identified using a rule such as a heuristic, user-defined rule. Rules selected by the user can be used to rank acronym and synonym pairs using factors such as occurrence frequency and maximum term length. A rule interpreter engine executes the user defined rule set to properly identify and retrieve the user selected acronym and synonym pairs through the utilization of a shallow pause read step. Finally, the user selected acronym and synonym pairs are ranked according to the user preferences, and can be displayed or held for subsequent use in searching.

The invention discloses a full text retrieval system based on natural language understanding, comprising: a database server, an information receiving judging module, a natural language processing module, a retrieving module, an indexing module, an index database and a result set processing module. The system of the invention provides two resolution strategies, that is, word classification static with semantic analysis associated with automatic segmentation and expanding inquired word static according to Hownet rule for low intelligence situation of current search engine. The deployed system converts information retrieval from current key word-based layer to knowledge (or concept)-based layer; the invention is capable of using techniques such as word classification, synonym, concept search, phrase identification, etc. with understanding and processing ability to knowledge. The search engine is provided with intelligence and humanization of information service. The user is allowed using natural language for information retrieval. The invention is capable of adding user selection behavior in interactive operation mode, so as to provide more convenient, more precise search service.

A device for hiding information in a text comprises a mechanicanism for providing the text, means for linguistically analyzing the text to produce text components, for determining a plurality of formulation alternatives for the text by varying the order of the text components and, optionally, in addition by using synonyms for text components, determining every formulation alternative is grammatically correct for the text and has essentially the same meaning as the text. Certain partial information is allocated to every sequence and/or to every synonym or to every paraphrase.

An intelligent information retrieval system for finding information components corresponding to an input query word. The system includes a synonym block for finding synonymous indexed keywords of the query word; an information indexing block for finding corresponding information components based on the indexed keyword; a component ranking-filtering block for ranking and filtering the found information components and outputting the desired information components being selected; a synonym adjusting block for adjusting the fuzzy mechanism of the synonym block based on the found information components; and a filtering adjusting block for adjusting the fuzzy mechanism of the ranking-filtering block based on the found information components. The aforementioned synonym block and information-indexing block are implemented by neuro-fuzzy networks for accelerating parallel processing and automatic learning. Further, the synonym block can tolerate input errors by way of query word encoding and position shift compensation.

The invention provides a method and a device for processing medical intelligent question and answer data, and relates to the technical field of intelligent questions and answers. The method includes extracting question keywords in user query question data; performing synonymy transformation, and determining synonym sets of the question keywords; performing matching lookup in a preset question andanswer knowledge base and a preset rule knowledge base according to the synonym sets of the question keywords; if succeeded, outputting answer result data corresponding to the question keywords and synonyms thereof in the synonym sets of the question keywords; if failed, subjecting the question keywords to semantic extension to acquire the question keywords and the synonym sets of hyponyms of thesynonyms; continuing matching lookup according to the question keywords and the synonym sets of the hyponyms of the synonyms, and generating a retrieval result list containing retrieval results; performing similarity calculation on the retrieval results in the retrieval result list to determine similarities among the retrieval results; sequencing and outputting the retrieval results according to the similarities of the retrieval results.

The invention discloses a multilayer quotation recommendation method based on a literature content mapping knowledge domain, and belongs to the field of information recommendation and intelligent information processing. The method comprises the following steps: firstly, obtaining the query requirement of a user, wherein the query requirement consists of the key words of the title and the digest of a thesis which needs to recommend a quotation thesis or quotation literature; then, on the basis of the literature content mapping knowledge domain, expanding and querying a retrieval word, wherein the mapping knowledge domain consists of the research object word and the research behavior word node of the literature, and edges which express various semantic relations including synonymy, synonym, an up and down position, part-whole, juxtaposition and the like; and finally, constructing the inverted index of the literature in a data set, selecting a candidate quotation, calculating the similarity between the candidate quotation and query, and adopting a gradient progressive regression tree to carry out quotation recommendation. The method carries out multilayer quotation recommendation on the basis of the literature content mapping knowledge domain, enlarges the range of the candidate quotation, accurately expresses the research object and contents of the thesis, improves efficiency for users to obtain a relevant literature and has a wide application prospect.

The invention discloses an electronic medical record text structuring method. The method comprises the following steps that 1, a medical knowledge database is loaded; 2, an electronic medical record text is read; 3, word segmentation is carried out on short sentences through a forwards maximum match algorithm, and words in sentences, word properties and relative position relations are obtained; 4, whether the semantics in the sentences for disease information description is positive or negative is judged; 5, disease information elements are extracted; 6, the steps 2-5 are repeated till all interesting contents in the electronic medical record are obtained; 7, different expressions of the disease information elements are combined, the same disease information is combined according to a medical synonym bank, and redundant information is removed; 8, disease description information elements are stored in a structure/class mode, the structuring process is finished, disease relevant information can be effectively extracted from medical record description text, structural expression for disease information is formed, and therefore disease occurrence regularity, definite diagnosis ways, treatment effects and the like are deeply explored.

The invention discloses a clustering method for question sentences in a question-and-answer platform and a system thereof. The technical scheme is as follows: the question sentences in the question-and-answer platform is analyzed according to the semantic feature of the question sentences to obtain analysis results; the semantic feature comprises the question type and the comparison feature of the question sentences and thesaurus correlative to the content of the question sentences; and aiming at the question sentences which is analyzed by the semantic feature, a clustering algorithm for evaluating the semantic similarity of the question sentences is adopted to obtain clustering results of the question sentences in the question-and-answer platform. The system comprises a question sentences analysis module and a clustering algorithm module. Aiming at the problem that the clustering method for the question sentences in the question-and-answer platform and the system thereof are not existed in the prior art, the technical scheme of the invention fills the gap, thereby not only realizing fast and exact clustering method and system in the question-and-answer platform, but also improving user experience.

The invention relates to a method and a system for uploading files. The method includes that a user selects files to be uploaded and submits hashed value of the files to be uploaded. A request for file uploading and based on HTTPOST is sent to a server. File type of the files to be uploaded is judged, the next step is conducted on yes judgment, and failure warning is returned to the user to finish uploading on no judgment. The method further includes recognizing content of the files to the uploaded, reminding the user that identical files exist, returning pre-existing file address and finishing uploading if identical files exist in the server, starting uploading if no identical files exist in the server, calculating the hashed value of the uploaded files, comparing the hashed value with submitted hashed value, reminding that file uploading succeeds, returning the file address to the user and finishing uploading if the values are identical, and returning the uploading failure warning and finishing uploading if the values are not identical. The method and the system resolve the problems of synonym file re-uploading, file type judgment, file verification and the like.

The invention discloses a method and a system for linking entities. The method includes acquiring to-be-linked entities from given texts; acquiring entity names and abbreviation word banks from preset knowledge bases and establishing synonym banks of the entity names on the basis of the preset knowledge bases; carrying out searching in the synonym banks by the aid of entity keywords; linking the entity keywords for searching and the entity names in the preset knowledge bases if a certain entry matched with the synonym banks is found by means of searching; generating candidate entities if the certain entry is not found by means of matching and carrying out disambiguation linking in context similarity evaluation modes. The synonym banks contain the entity names acquired from the preset knowledge bases and information data related to the entity names. The entity keywords are acquired by means of word segmentation and are used as search terms. The entity names in the knowledge bases correspond to the entry. The method and the system in an embodiment of the invention have the advantage that the entity linking accuracy can be improved.

A writing advisor program (20) receives a proposed text in an author's second language (L2) and determines at least one candidate replacement word for a selected word based on a determined language model (p(c)) and a determined corruption model (p(r|c)). The determined language model reflects correct usage of the text in the second language, independent of the native or first language (L1) of the author, based on (L2) corpora. The determined corruption model is based on some a priori knowledge about probable corruption paths leading the author to realize some inadequate expression in the second language instead of the correct, intended expression. Different types of corruption paths may be used that include bidirectional translations, false-friends, synonyms, common semantic features, second language internal cognates, preposition alternatives, and first language inserts.

The invention discloses a method for automatically creating a keyword index table. The method includes subjecting a file to be translated to word segmentation process to obtain a word list of the file, and subjecting the word list to part-of-speech tagging; filtering candidate keywords in the word list to obtain a coarse candidate word collection and codes of each sense of the candidate keywords; subjecting the candidate keywords to synonym chain construction according to semantic similarity of the words to obtain a synonym chain collection; acquiring word weight of vocabularies in the synonym chain collection and extracting keywords to form a keyword collection according to the word weight; and comparing the keyword collection with an existing reference library keyword index collection, providing a relevant file collection if the existing reference library keyword index collection contains the candidate keywords, otherwise, adding the candidate keywords to the reference library keyword index collection, and simultaneously, creating an index. Compared with traditional keyword extraction methods, the method has the advantages that precision rates and recall rates are obviously increased.

The invention puts forward a synonym expansion method and device for search information. The method comprises the following steps that: carrying out word segmentation processing on the search information to obtain at least one segmented word of the search information; obtaining the candidate synonym set of the segmented word, wherein the candidate synonym set comprises at least one synonym of thesegmented word; forming a synonym pair which contains the synonym and the segmented word by aiming at each synonym; carrying out feature extraction on the synonym pair to obtain a synonym pair featureset; according to the feature set, predicting the synonym pair to obtain a target probability that the synonym pair is predicted as reasonable replacement; and if the target probability exceeds a preset threshold value, forming a synonym expansion item by the segmented word and the synonym, and searching and obtaining a search result on the basis of the synonym expansion item. Through the method,synonym replacement rationality and accuracy can be improved, the recall rate and the accuracy of a search result are improved, and therefore, the technical problems in the prior art that synonym replacement is inaccurate and a search result recall rate is poor can be solved.

The invention belongs to the technical field of processing or transformation of natural languages, and discloses a data-enhanced machine translation method based on similar word and synonym replacement. The characteristics that word vectors are finally clustered well are utilized to obtain a similar word table and a synonym table with high quality; the similar word table and the synonym table areconstructed using the word vectors obtained in the training process of a large language, and similar words and synonyms in a scarce small language are replaced; a parallel corpus of the small languageis expanded, and a neural network machine translation model of the small language is trained by the adoption of an encoding-decoding structure and a neural network of an attention mechanism. Trainingdata is expanded, parameters of a neural network translation model can be well studied in enough data, and the problem of unregistered words in the neural machine translation can be alleviated, so that the translation quality of the translation model is improved. When the translation quality of the entire network on a development set is no longer significantly improved, the network parameters have been well studied.