1196 results about "Word list" patented technology

Disclosed is a semantic user interface system that allows text information to be tagged with machine-readable IDs that are associated with concepts for conveying information without any ambiguity or without being hampered by the limitations of human languages. Typically, a plurality of vocabularies are stored across a network, and each vocabulary includes a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID. An input interface accepts text information, selects those machine-readable IDs whose keywords match up with the text information, and returns a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description. The machine-readable IDs can carry information in the form of concepts without any ambiguity as opposed to text information. This system can be applied to web and database searches, publishing messages to selected subscribers, interfacing of applications software, machine translations, etc.

A clustering architecture that dynamically groups the search result documents into clusters labeled by phrases extracted from the search result snippets. Documents related to the same topic usually share a common vocabulary. The words are first clustered based on their co-occurrences and each cluster forms a potentially interesting topic. Keywords are chosen and then clustered by counting co-occurrences of pairs of keywords. Documents are assigned to relevant topics based on the feature vectors of the clusters.

A system and method for automated dictionary population is provided to facilitate the entry of textual material in dictionaries for enhancing word prediction. The automated dictionary population system is useful in association with a mobile device including at least one dictionary which includes entries. The device receives a communication which is parsed and textual data extracted. The text is compared to the entries of the dictionaries to identify new words. Statistical information for the parsed words, including word usage frequency, recency, or likelihood of use, is generated. Profanities may be processed by identifying profanities, modifying the profanities, and asking the user to provide feedback. Phrases are identified by phrase markers. Lastly, the new words are stored in a supplementary word list as single words or by linking the words of the identified phrases to preserve any phrase relationships. Likewise, the statistical information may be stored.

Method and apparatus for improving a user's ability to spell words correctly are provided. The method comprises: displaying a word list for user selection of a correctly spelled word; and displaying assistance information associated with the correctly spelled word. In one embodiment, the assistance information is selected from: one or more root words, one or more related words, and one or more memorization clues. The apparatus may comprise a signal bearing medium containing instructions of a computer program which, when executed by one or more processors, performs the method of the invention. Another embodiment of the apparatus comprises a computer system comprising one or more processors and memory configured to execute a computer program which, when executed, performs the method of the invention.

A computerized pronunciation system is provided for generating pronunciations for words and storing the pronunciations in a pronunciation dictionary. The system includes a word list including at least one word; transcribed acoustic data including at least one waveform for the word and transcribed text associated with the waveform; a pronunciation-learning module configured to accept as input the word list and the transcribed acoustic data, the pronunciation-learning module including: sets of initial pronunciations of the word, a scoring module configured score pronunciations and to generate phone probabilities, and a set of alternate pronunciations of the word, wherein the set of alternate pronunciations include a highest-scoring set of initial pronunciations with a highest-scoring substitute phone substituted for a lowest-probability phone; and a pronunciation dictionary configured to receive the highest-scoring set of initial pronunciations and the set of alternate pronunciations.

An acronym expansion system of the present invention receives electronic documents and extracts acronyms and their corresponding expansions. A part-of-speech tagger decomposes text into string tokens or words and tags them with their part-of-speech, while an acronym identifier determines whether a word is a potential acronym based on various conditions. An expansion identifier retrieves lists of words preceding and following a potential acronym to search for the expansion. The resulting word lists are examined sequentially to identify and retrieve an expansion for the potential acronym. An expansion extractor receives the potential acronym and a processed word list to retrieve the expansion of the potential acronym from that list. The extractor may utilize information from prior search iterations, and verifies an extracted expansion against a set of rules to remove spurious expansions.

In one aspect, the invention is directed to an interactive method for teaching a foreign language. The method includes displaying a translation of a target word selected by a user from a reading material, testing the user's assimilation of the target word, evaluating results of the testing to obtain an evaluation outcome; and adding the target word to an active vocabulary associated with the user or retaining the target word as unassimilated, depending on the evaluation outcome. Testing can be based on recognition or reproduction techniques. In preferred examples, the method further includes providing the reading material. In another aspect, the invention is related to a system for teaching a foreign language, the system including a link for requesting and receiving translation of a word from a global vocabulary and a module capable of generating drill exercises for prompting assimilation of the word.

The embodiments of the present invention provide a computer-implemented method and system for translating user keywords into semantic queries based on domain vocabulary. The system receives the user keywords and search for the concepts. The concepts are transformed into a connected graph. The user keywords are translated into precise access paths based on the information relationship described in conceptual entity relationship models and then converts these paths into logic based queries. It bridges the semantic gap between user keywords and logic based structured queries. It enables users to interact with the semantic system by articulating the information in a structured query language. It improves the relevance of search results by incorporating semantic technology to drive the mechanics of the search solution.

A method and system are provided for translating terms from a source language to a target language utilizing a community of contributors. The source language terms are stored in an active glossary (400), the translation of which may be governed by an administrator. A community of contributors suggests translations for terms in the active glossary (400). A moderator selected by the administrator moderates translation of the terms in the active glossary (400) into the target language. Accordingly, the moderator may, in the exercise of his or her judgment, lock a particular suggested translation, making it the final translation for a term in the source language. Upon satisfaction of some predetermine exit criteria, e.g., a time deadline or completion threshold, the active glossary (400) is locked and all of the final translations for terms in the source glossary selected by the moderator are then stored in a localized glossary (500).

In a speech training and recognition system, the current invention detects and warns the user about the similar sounding entries to vocabulary and permits entry of such confusingly similar terms which are marked along with the stored similar terms to identify the similar words. In addition, the states in similar words are weighted to apply more emphasis to the differences between similar words than the similarities of such words. Another aspect of the current invention is to use modified scoring algorithm to improve the recognition performance in the case where confusing entries were made to the vocabulary despite the warning. Yet another aspect of the current invention is to detect and warn the user about potential problems with new entries such as short words and two or more word entries with long silence periods in between words. Finally, the current invention also includes alerting the user about the dissimilarity of the multiple tokens of the same vocabulary item in the case of multiple-token training.

A system and method of providing an autocomplete recommended word, which classify a recommended word list according to indexes of various languages, store the recommended word list for each index, extract a corresponding autocomplete recommended word according to a user query and a setting mode which is received from a user's web browser, provide the user with the corresponding autocomplete recommended word, and thereby may propose a suitable recommended word according to the user query.

A method, computer readable medium and system are provided which collect new words for addition to a lexicon for an agglutinative language. Sentences in the agglutinative language are retrieved from documents, for example from web pages. New word candidate character strings are identified in the retrieved sentences. The identified new word candidate character strings are filtered using a combination of a plurality of statistical criteria to generate a new words list. Words from the new words list are added to the lexicon.

Enhancing queries for information retrieval that automatically finds the preferred, first ranked matching term usage subject area (“TUSA”) from a prior query. The process automatically finds alternative TUSAs for the prior query, ranked by degree of match or preference, and provides an option to switch among the alternative TUSAs. It is required that a TUSA for the query be passively accepted or actively selected from a presented list based on the prior query. Using means prepared in advance from data sets of messages collected for each TUSA and general vocabulary the process also ranks and presents to the user alternative and additional query terms and phrases reflecting specificity and relevance to the query and the TUSA. Significantly relevant terms and phrases are presented for query refinement and ranked by relevance permitting the user to select and deselect query terms and effect a new search based on the enhanced query.

The software incorporates a glossary management tool that makes it easy for each client to customize terminology to the needs of a particular business. With this tool, termed a glossary manager, a company can customize a number of feature names in the system to provide a more familiar context for their users. A system administrator can also customize the manner in which “thumbnail” or “preview” images are presented. The system performs clustering on search queries, and searches media records multi-modally, using two or more approaches such as image searching and text searching. An administrator can tune search parameters. Two or more streams of metadata may be aligned and correlated with a media file, facilitating later searching. The system evaluates itself. It folds popularity information into rankings of search results.

The invention discloses a data search method and a data search system. The data search method comprises the following steps: pre-extracting a key word list, obtaining query results corresponding to key words in the key word list through visiting an external data source server, and associatively storing the key words and the query results corresponding to the key words in a cache database; obtaining a search request with a search word sent by a client, distributing the search request to the cache database, searching the key word matched with the search word and the query result corresponding to the key word according to a preset matching rule in the cache database; and sending the query result corresponding to the key word to the client. According to the data search method and the data search system, the problem of excessively long waiting time of a user caused by application of a complex algorithm to completion of a data matching process when an information database and an index database are configured at the same time in the prior art can be solved, and the benefit of quickly searching matched data according to the preset cache database and the matching rule can be obtained.

The invention discloses an implementation method of a fusion network question and answer system based on a multi-attention mechanism, which comprises the following steps of constructing a question andanswer system network model, preprocessing an original data set to obtain a standby data set, and performing text length distribution analysis; subjecting text in standby data set to one-hot vector representation, using a CBOW model to train one-hot word vector and forming a word2vec word list; adjusting the sequence length of each sentence in the text, and adding a sentence end mark; training the word2vec vector by using an ELMO language model to obtain an ELMO word vector; encoding the ELMO vector to obtain a sentence vector; performing coarse-fine granularity attention on the sentence vectors respectively to obtain memory vectors and attention vectors based on each word; carrying out vector splicing to obtain expression vectors based on words and sentences; and decoding an answer representing the vector generation question sentence. According to the method, the representation ability of sentences is improved through an ELMO language model; and various attention mechanisms are fused, so that the decision making accuracy of the system is improved, and the interpretability of the system is enhanced.

The invention belongs to the technical field of computer software and discloses a multi-language-pair neural network machine translation method and system. A plurality of bilingual parallel corpora ofa same language system are utilized and mapped to a same high-dimensional vector space after byte pair encoding, so that multiple languages share a same semantic space, the size of a word list is reduced, model parameters are reduced, and convergence of a model is accelerated. Words of a same language family are in the same vector space, more information can be learned mutually, the information which can not be learned through only certain bilingual parallel corpora can be learnt, and the quality of word vectors is improved. The machine translation system can be used for translation in the language direction without direct bilingual parallel corpora, and the translation quality in the scarce parallel corpus translation direction is greatly improved through mutual information learning. Meanwhile, the same model is used for translation for the translation direction low in utilization rate, occupation of a server is reduced, and the utilization rate of the server is increased.

The invention provides a word vector training method and device. The method comprises the following steps: an internet webpage is captured, and training language materials are acquired and stored in a corpus; each training language material in the corpus is subjected to word segmentation, and an orderly word set corresponding to each training language material is obtained; a word list is established according to pre-collected user query logs; the training language materials stored in the corpus are distributed to nodes of a distributed word vector learning model; the distributed word vector learning model is configured to perform periodic word vector training on each word in the word list, and the word vector corresponding to the word in the word list is obtained. According to the word vector training method and device, the word vectors obtained through training can be well applied to search business, and fast iterative high-quality word vector training can be realized.

An online-increment evolution topic model based automatic software classifying method includes acquiring relevant software texts, grouping and preprocessing by a preset time slice; generating a probability model of an online evolution topic model, computing the number of the optimum topics according to project description texts grouped according to the time slice, and incrementally computing topic word distribution and topic text distribution of the project description texts within the current time slice; acquiring a text d of an unknown classifying topic, computing topic word distribution of n topics subordinative to the text d according to the topic word distribution and the topic text distribution, classifying the text d into corresponding topics, and automatically adding semantic tags to the topics based on the word list and word inquiry method, and finally completing classification of software projects. By the online-increment evolution topic model based automatic software classifying method, new topics appearing in open source communities can be found in time, software projects can be automatically classified, a software developer can search out required open source software projects according to software topics conveniently, and accordingly, software development efficiency is improved, and quality and assurance of the open source communities are improved.

A computer-implemented system and method is disclosed for retrieving documents using context-dependant probabilistic modeling of words and documents. The present invention uses multiple overlapping vectors to represent each document. Each vector is centered on each of the words in the document and includes the local environment. The vectors are used to build probability models that are used for predictions of related documents and related keywords. The results of the statistical analysis are used for retrieving an indexed document, for extracting features from a document, or for finding a word within a document. The statistical evaluation is also used to evaluate the probability of relation between the key words appearing in the document and building a vocabulary of key words that are generally found together. The results of the analysis are stored in a repository. Searches of the data repository produce a list of related documents and a list of related terms. The user may select from the list of documents and/or from the list of related terms to refine the search and retrieve those documents which meet the search goal of the user with a minimum of extraneous data.