115 results about "Proper noun" patented technology

A computer implemented system and method for processing text are disclosed. Partially processed text, in which named entities have been extracted by a standard named entity system, is processed to identify attributive relations between a named entity or proper noun and a corresponding attribute. A concept for the attribute is identified and, in the case of a named entity, compared with the named entity's context, enabling a confirmation or conflict between the two to be determined. In the case of a proper name, the attribute's context can be associated with the proper name, allowing the proper name to be recognized as a new named entity.

A system and method for natural language processing of queries are provided. A lexicon includes text elements that are recognized as being a proper noun when capitalized. A natural language query includes a sequence of text elements including words. The query is processed. The processing includes a preprocessing step, in which part of speech features are assigned to the text elements in the query. This includes identifying, from a lexicon, a text element in the query which starts with a lowercase letter and assigning recapitalization information to the text element in the query, based on the lexicon. This information includes a part of speech feature of the capitalized form of the text element. Then parts of speech for the text elements in the query are disambiguated, which includes applying rules for recapitalizing text elements based on the recapitalization information.

The present invention provides an improved method and apparatus for translating a source language to a target language. The invention uses placeables (e.g., proper nouns, titles and names, dates, times, units and measurements, numbers, formatting information, such as tags or escape sequences, styles, graphics, hyperlinks) to assist a translator by not having to retype information that does not need to be translated and to provide conversions to the target locale if necessary like for speeds.

The autonomous avatar driver is useful in association with language sources. A sourcer may receive dialog from the language source. It may also, in some embodiments, receive external data from data sources. A segmentor may convert characters, represent particles and split dialog. A parser may then apply a link grammar, analyze grammatical mood, tag the dialog and prune dialog variants. A semantic engine may lookup token frames, generate semantic lexicons and semantic networks, and resolve ambiguous co-references. An analytics engine may filter common words from dialog, analyze N-grams, count lemmatized words, and analyze nodes. A pragmatics analyzer may resolve slang, generate knowledge templates, group proper nouns and estimate affect of dialog. A recommender may generate tag clouds, cluster the language sources into neighborhoods, recommend social networking to individuals and businesses, and generate contextual advertising. Lastly, a response generator may generate responses for the autonomous avatar using the analyzed dialog. The response generator may also incorporate the generated recommendations.

A method of utilizing metadata stored in a computer-readable medium to assist in the conversion of an audio stream to a text stream. The method compares personally identifiable data, such as a user's electronic address book and/or Caller/Recipient ID information (in the case of processing voice mail to text), to the n-best results generated by a speech recognition engine for each word that is output by the engine. A goal of this comparison is to correct a possible misrecognition of a spoken proper noun such as a name or company with its proper textual form or a spoken phone number to correctly formatted phone number with Arabic numerals to improve the overall accuracy of the output of the voice recognition system.

Extended internal domain name service of URI taking distributed service scheme, wherein site names or proper nouns that are not formal top-level domains are used as top-level domains. A central name server, a local name server and a user computer, each of which is loaded with a program for domain service. A service preparation step, the local name server registers a name and address of a site into the central name server and is given a top-level domain from the central name server. A name registration step, the local name server gives names to resources inside a site or site user registers names of information into the local name server. A domain inquiry step, the user computer inquires internal domains of particular local name server without confusion to existing domain service when user inputs internal domains according to a domain scheme.

The invention relates to a device for assisting judicial case judgment based on machine learning, which utilizes a large amount of document data and trains a model to learn the relationship between case fact description and the fine range and relevant legal provisions, and realizes the prediction of the fine range and the law label of any given case fact description text. The invention relates toa device for assisting judicial case judgment based on machine learning. Including: defining the proper nouns in the description of the facts of a given case and dealing with them; Extracting multiplesemantic features from the text to achieve a deeper level of semantic representation; Machine learning method based on multi-label classification is used to classify the law items and obtain the lawlabels related to the description text of the case facts. Single-label classification training model based on machine learning predicts the range of possible fines in related cases. The invention applies machine learning to the judicial field for the first time, realizes deeper semantic representation by multiple feature extraction modes, improves the accuracy and generalization ability of the training model well, has higher reference significance for the final judgment of a case, and is conducive to the realization of the same case and the same judgment.

A Chinese word segmentation method based on navigation information retrieval is characterized in that a word segmentation system is obtained through the steps that a dictionary is loaded, and text code conversion is carried out; segmentation processing is carried out, and a source character string is segmented into a plurality of slightly simpler short sentences; atomic word segmentation is carried out to obtain the smallest morpheme units which cannot be segmented in the short sentences; word forming full-match is achieved with a word-by-word traversal matching method; the matching results are screened to generate a plurality of best results; human names, place names and proper nouns are processed; the dictionary is corrected, and mainly, unlisted new words are added, and properties of the existing words are improved; the processing results of all the short sentences are finally combined to be output. The Chinese word segmentation method has the advantages that content input by a user can be formed into words through the Chinese word segmentation technology, the speed can be optimized, wrongly written characters can be corrected with the words as the basis, and a more suitable result can be provided. With the Chinese word segmentation technology, semantics can be understood by an information retrieval engine better, and the provided result set can be fully adjusted.

A method, device, and computer program product for detecting negative opinions in social media, computer program product, and computer. Negative opinions in social media can be precisely detected at an early stage. A method for processing, with a computer, a plurality of messages sent by a plurality of users over time includes the following steps: obtaining a plurality of messages, each including a specific proper noun; determining a politeness level of each of the plurality of messages, each including the specific proper noun; and calculating a proportion of messages having a politeness level lower than a certain threshold with respect to the plurality of messages, each including the specific proper noun.

When a character string for a street search is input in a vehicle navigation apparatus, street data are searched, and all streets which include the character string for the street search in the formal street name character string are extracted. The extracted street is displayed, in a list format on a display screen, by using a portion of the formal street name string that is registered as a proper noun part of the formal street name character string. The extracted streets are sorted in the list format so that a street with the proper noun part including the character string for searches comes to the top of listing of the extracted streets, thereby making it easy to find out a desired street in the listing of the extracted streets.

The invention discloses a word segmentation processing method and device, a mobile terminal and a computer readable storage medium. The method comprises the following steps of: when a to-be-segmentedstatement is obtained, determining a target language type corresponding to the to-be-segmented statement; respectively first feature vectors corresponding individual characters, second feature vectorscorresponding to two words and third feature vectors corresponding to proper nouns in the to-be-segmented statement; determining current fourth feature vectors of the individual characters accordingto the first feature vectors, the second feature vectors and the third feature vectors; and carrying out word segmentation on the to-be-segmented statement according to a preset Chinese character label transfer matrix and the current fourth feature vectors of the individual characters. According to the method, word segmentation is carried out on to-be-segmented statements according to target language types corresponding to the to-be-segmented statements, so that the correctness of carrying out word segmentation on to-be-segmented statements in various language types is improved; and proper resources can be loaded according to requirements, so that storage spaces of mobile terminals are saved and the user experience is improved.

The invention provides a deep learning-based text similarity detection method for a financial industry, and the method comprises the steps: S1, building a special noun lexicon, obtaining a conditionalprobability model based on a conditional random field, and carrying out the probability calculation through the conditional probability model; S2, using a Bi-LSTM-RNN model to take out each word in the sentence according to the sequence, extracting the information of the word, and embedding the information into a semantic vector, thereby obtaining the semantic representation of the sentence; S3,analyzing a logic structure of the sentence according to the semantic information extracted by the neural network, organizing the sentence into a tree structure, and finally expressing the paragraph according to a vector tree mode; and S4, matching the vector tree extracted from the text with a historical data document in a database, and comparing similarities from two angles respectively, one being the similarity between the vector trees, and the other being the similarity between every two nodes, so as to finally obtain a result.

The invention discloses an integrated automatic lexical analysis method for ancient Chinese texts. The method includes the following steps: pre-training the word vector of the ancient Chinese with semantic features by using the Word2Vec model; adding the information data appearing in the historical documents to the ancient name database to form a number of proper noun entries; adjusting Bi-LSTM- Each parameter of the CRF neural network model preprocesses the final training corpus into a model readable form, loads into the neural network model, continuously iteratively learns, and automaticallyevaluates the labeling result of the test corpus. According to the method, a sentence segmentation, word segmentation and part-of-speech tagging integrated tagging method is adopted, the repeated tagging process of lexical analysis of multiple sub-tasks is omitted, and multi-stage diffusion of repeated tagging errors is also avoided; According to the method, a deep learning model is adopted, richlanguage features can be learned automatically, and the work of manually customizing a feature template in traditional machine learning is omitted; The labeling model is accelerated by adopting GPU hardware, the model training time can be greatly shortened, and the efficiency is much higher than that of a traditional machine learning model.

A Chinese to English Translation Tool (CETT) locates pre-existing translations of phrases and increases probabilities for a match by searching independently of proper nouns and Western characters. The CETT comprises an enhancement program, a search program and a display program. The CETT is adapted to access a translation database, a proper noun table, and an unmatched translation table. The translation database is a central repository of an accumulated body of translated literature. The proper noun database is a table showing the associations between English and Chinese for proper nouns.

The embodiment of the invention provides a text error correction method and device, equipment and a storage medium. The method comprises the steps of replacing at least one obfuscated character in a to-be-corrected text by adopting a preset obfuscated character library to obtain a first text set; in the first text set, candidate texts meeting preset conditions are determined; replacing at least one obfuscated character in the candidate text by adopting the preset obfuscated character library to obtain a second text set; according to the second text set, traversing a domain lexicon storing at least two words which are the same as the domain to which the text to be corrected belongs to obtain a target text matched with the second text; therefore, the text to be corrected is corrected by adopting the confused word stock and the domain word bank, and the domain proper nouns can be corrected, so that the accuracy of correcting the text is improved.

The invention discloses a construction method for an aircraft state monitoring wireless sensor network, relates to a construction technology for the aircraft state monitoring wireless sensor network, and aims to construct a wireless sensor network on an aircraft in order to meet the demand of aircraft state monitoring. The method comprises the following steps that: a terminal node transmits a DODAG (Destination Oriented Directed Acyclic Graph) Information Solicitation (DIS), and collects information of all neighbor nodes within a range; the neighbor nodes start to transmit DODAG information object (DIO) packets after the DIS is received; a request node caches all the received DIO packets, updates a neighbor table of the request node, calculates relative distances between the neighbor nodes and a root according to a calculation result of a target function, and selects a proper node; meanwhile, nodes receiving a route request establish backward paths for sub-nodes, and transmit DODAG advertisement object (DAO) packets to selected father nodes to instruct the father nodes that the nodes are sub-nodes of the father nodes; and the father nodes transmit the DAO packets to father nodes of the father nodes after updating routing tables of the father nodes till the main node. The method is suitable for aircraft state monitoring occasions.