109 results about "Noun phrase" patented technology

A method, system, and apparatus are provided for creating a knowledge interchange (“KI”) profile for a user that identifies the interests of the user, the individuals with which the user has communicated, and the topics on which the communication with the user was made. In order to create the KI profile, items of interest are gathered at the client computer by monitoring the interaction between a user and programs executing on the client computer. Once the items of interest have been identified, the KI profile is created by performing a social network analysis, an interest analysis, and a noun phrase analysis. Once the KI profile has been created, it may be uploaded to a server computer where it is aggregated with KI profiles created for other users.

A method and system for extracting opinions about a subject of interest from a text document in which each sentence is analyzed individually to identify the opinions. The most relevant feature terms related to the subject are extracted from the document based on their relevancy scores. Candidate feature terms are definite noun phrases at the beginning of the sentences. For each sentence that refers to the subject or a feature term, the invention determines whether the sentence includes an opinion polarity about the subject or the feature term. The opinion polarity is detected by identifying opinion terms in the sentence using an opinion dictionary or an opinion rule base, parsing the sentence with an English parser to identify grammatical components in the sentence and their relationships, and finding a matching entry in the dictionary or the rule base.

An apparatus is provided that includes a processor and a memory. The processor is configured to determine a category for a group of isolated noun phrases in a structured or semi-structured data source stored in the memory. The group of isolated noun phrases includes one or more isolated noun phrases. The processor is also configured to translate the group of isolated noun phrases from a source language to a target language using a category-driven isolated noun phrase translation. The determination of the category and the category-driven isolated noun phrase translation are performed based on context derived from the group of isolated noun phrases.

There is disclosed a method of facilitating interaction between users of an electronic community. In an embodiment, the method comprises: reviewing a user activity log for each user in the electronic community; executing a natural language parser to extract significant noun phrases from the user activity log; updating user profiles from the newly extracted noun phrases, based on their usage frequency and importance value; and storing the updated profiles in a user profile and relationship data base; and executing a similarity based clustering algorithm to cluster user profiles, thereby discovering relationships among users and storing them in a user profile and relationship database. The method may further comprise displaying for each user the one or more relationships to which the user is assigned, together with a list of users assigned to the one or more relationships. The method may also comprise storing for each user the relationship to which the user is assigned in a user profile and relationship database.

Coreference resolution is the process of identifying when two noun phrases (NP) refer to the same entity. Two main contributions to computational coreference resolution are made. First, this work contributes a new method for recognizing when an NP is anaphoric. Second, traditional approaches to coreference resolution typically select the most appropriate antecedent by recognizing word similarity, proximity, and agreement in number, gender, and semantic class. This work contributes a new source of evidence that focuses on the roles that an anaphor and antecedent play in particular events or relationships. I show that using contextual role knowledge as part of the coreference resolution process increases the number of anaphors that can be resolved, and I demonstrate an unsupervised method for acquiring contextual role knowledge that does not require an annotated training corpus. A probabilistic model based on the Dempster-Shafer model of evidence is used to incorporate contextual role knowledge with traditional evidence sources.

A method, system, and apparatus are provided for maintaining user privacy in a knowledge interchange (“KI”) system. A user may provide privacy preferences relating to their participation in the KI system. The user may identify specific keywords, noun phrases, and contacts that should not be transmitted to a server computer. The user may also specify whether each keyword, noun phrase, or contact should be public or private. If a public keyword is identified during a search query as being associated with the user, the user's identity will be made available to a seeker If a private keyword is identified during a search query as being associated with the user, the user's identity will not be made available and a brokered communication process between the seeker and the user will be performed.

The invention provides an automatic legal knowledge graph construction method, and aims at automatically constructing legal knowledge graphs according to trial documents. The method comprises the following steps of carrying out stop word removal and word segmentation on obtained trial documents; respectively extracting subject words of three types of trial documents, carrying out part-of-speech tagging and filtration on the extracted subject words, and extracting noun or noun phrase subject word to serve as entity concepts of a legal knowledge graph according to the filtration result; obtaining words similar with each extracted noun or noun phrase subject word, carrying out part-of-speech tagging and filtration on the obtained similar words, and extracting noun or noun phrase subject word similar words as entity concepts of the legal knowledge graph according to the filtration result; and constructing the legal knowledge graph according to the extracted subject word entity concepts, the similar word entity concepts and triple structures such as subject word-subject relationship-subject word and subject word-similar relationship-similar word formed by a relationship between the subject word entity concepts and the similar word entity concepts. The invention relates to the technical field of knowledge engineering.

Techniques for displaying interactive topic-based summarization are provided. A text to be summarized is segmented. Discrete keyword, key-phrase, n-gram, sentence and other sentence constituent based summaries are generated based on statistical measures for each text segment. Interactive topic-based summaries are displayed with human sensible omitted text indicators such as alternate colors, fonts, sounds, tactile elements or other human sensible display characteristics useful in indicating omitted text. Individual and/or combinations of discrete keyword, key-phrase, n-gram, sentence, noun phrase and sentence constituent based summaries are dynamically displayed to provide an overview of topic and subtopic development within a text. A hierarchical and interactive display of texts based on the use of discrete sentence constituent based summaries which associates expansible and contractible displayed text to provide contextualized access to an interactive topic-based text summary and to an original text.

A network text analysis called center resonance analysis (CRA) is presented which represents texts (or transcribed conversations) as networks of centering words. The networks of centering words are components of utterances or (specifically noun phrases) that authors and/or speakers deploy in a manner that makes their utterances coherent. A CRA network can be derived for any text, and abstractly represents its main concepts, their influence, and their interrelationships.

A system and method identify base noun phrases (baseNP) in a linguistic input. A part-of-speech tagger identifies N-best part-of-speech tag sequences corresponding to the linguistic input. A baseNP identifier identifies baseNPs in the linguistic input using a unified statistical model that identifies the baseNPs, given the N-best POS sequences.

A phrase-based statistics machine translation method includes for phrases in an input sentence, performing fuzzy matching in a pre-constructed phrase table. In the method, by performing fuzzy matching on the phrases, high quality translations can be generated for long phrases in the input sentence, thus the quality of the translation can be effectively increased with respect to the machine translation systems based on phrase exactly matching.

The invention relates to a similar articles recommendation method based on a theme model. Firstly, an original text preprocessing is conducted, a simple content of an article is extracted; then, the content of the article is divided into words, an analysis of the properties of the words is conducted, noun phrases are filtered out, a word bag is extracted, a main word feature vector is formed; next, a TFIDF model is trained with the word feature vectors of all articles, based on the TFIDF model, the word feature vector of each article is calculated, a TFIDF feature vector is formed; again, an LSI theme model is trained with the TFIDF feature vectors of all articles; finally, the LSI model is used to calculate, potential theme feature vectors of the article are obtained, similar articles canbe obtained from the calculation of the vector similarity. The method can help Internet users to find interesting articles effectively, and has the advantages of a wider range of application, lower manual marking cost, better recommendation diversity and the like.

The invention discloses a multilingual information extraction method adopting a hierarchical pipeline filter system structure. In the method, the linguistic material to be processed is identified by a multilingual automatic identifying member; then four simple named entities, which are time, date, percent and amount of money, are identified by a simple named entity identifying member; a person name and a place name are extracted by a person name and place name identifying member; then, participialization is performed by a lingual independent participializing member; part-of-speech tagging is performed by a part-of-speech tagging member; an organization name is identified by an organization name identifying member; and the longest noun phrase is identified with a longest noun phrase identifying member. The method provides a practical basic framework for an information extraction system, so that the problems of reusing and generalization of a plurality of overlapped algorithms are solved successfully; reusability, maintainability and extensibility of software is improved; and the research and development efficiency of the information extraction system is improved.

A method of generating caption abstract, including: generating a target text from a predetermined caption, analyzing a morpheme of a word included in the target text, and analyzing a grammatical structure of the target text by referring to the morpheme; extracting and removing low content words from the target text by using the morpheme or information on the grammatical structure and determining a main predicate; extracting a major sentence component with respect to the main predicate by referring to the information on the grammatical structure, as a candidate abstract word; substituting a relevant word for a complex noun phrase or a predicate phrase from the candidate abstract words by referring to a predetermined database; and generating an abstract by rearranging the candidate abstract words according to a predetermined rule.

The present invention discloses a generation method and apparatus for a medium-and-long phrase in a domain lexicon, relates to the field of natural language processing, and solves the problem that medium-and-long phrase cannot be generated in the process of constructing a domain lexicon in a conventional way. The method disclosed by the present invention comprises: acquiring a general corpus and a domain corpus; performing Chinese word segmentation on the two corpora, and combining word segmentation results to obtain medium-and-long phrase candidate character strings; collecting statistical data of each medium-and-long phrase candidate character string in the general corpus and in the domain corpus; and according to the statistical data of each medium-and-long phrase candidate character string, calculating a chi-square statistic of each medium-and-long phrase candidate character string to obtain a score thereof, and comparing the score with a set condition, and retaining a medium-and-long phrase candidate character string that meet the condition as a domain word of a domain lexicon. The method and apparatus disclosed by the present invention are mainly used in the process of generating the medium-and-long phrase in the domain lexicon.

The invention discloses a neural machine translation method based on a user dictionary, and the method comprises the steps: crawling mass data from a network through a web crawler technology, and obtaining a bilingual word pair from a corpus through an extraction technology to construct the user dictionary; Using a user dictionary to perform dictionalization on the training corpus, extracting thetraining corpus, and mixing the extracted training corpus with the original corpus to serve as input of neural network model training; Performing consistency detection on the user dictionary placeholders contained in the sentence pairs; Processing the training data by using a user dictionary, inputting the training data into a neural network model, and starting to train the model until the model converges; And inputting a sentence containing the user dictionary, obtaining dictionary information to replace the placeholder, and translating at the same time to obtain a high-precision translated text matched with the information in the user dictionary. During translation, the high-precision requirements of different users on noun phrases and named entities are well met, and the user-defined dictionary library is added according to the requirements and translation habits of the users, so that the high-quality requirements of the different users on translated texts are met.

The invention discloses a method and a system for translating integral patent documents. The method includes acquiring phrases by a template-based or rule process or a weight process; modifying the phrases by a phrase frequency process or a modified phrase frequency process or a memory reference process or the like to finally obtain recognized noun phrases RNP; marking RNP information for the recognized noun phrases in a full text, translating the recognized noun phrases RNP and storing relevant information in a phrase memory; translating the full text sentence by sentence and directly fetching translated texts from the phrase memory without spreading phrases marked with the RNP information; sequentially outputting the translated texts according to title information of the original text after the full text is completely translated. The method and the system have the advantages that commonly used complicated noun phrases in the patent documents can be acquired, so that analysis time for sentences containing the commonly used complicated noun phrases can be shortened, the translation speed can be increased, and the translation consistency of the commonly used complicated noun phrases can be guaranteed.