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 correcting errors in a speech recognition system includes a process of searching a speech recognition error-answer pair DB based on a sound model for a first candidate answer group for a speech recognition error, a process of searching a word relationship information DB for a second candidate answer group for the speech recognition error, a process of searching a user error correction information DB for a third candidate answer group for the speech recognition error, a process of searching a domain articulation pattern DB and a proper noun DB for a fourth candidate answer group for the speech recognition error, and a process of aligning candidate answers within each of the retrieved candidate answer groups and displaying the aligned candidate answers.

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.

The present invention provides a method and apparatus for training a parsing statistic model, a method and apparatus for transliteration. Said parsing statistic model is to be used in transliteration between a single-syllable language and a multi-syllable language and includes sub-syllable parsing probabilities of said multi-syllable language. Said method for training the parsing statistic model comprising: inputting a bilingual proper name list as corpus, said bilingual proper name list includes a plurality of proper names of said multi-syllable language and corresponding proper names of said single-syllable language respectively; parsing each of said plurality of proper names of multi-syllable language in said bilingual proper name list into a sub-syllable sequence using parsing rules; determining whether said parsing is correct according to the corresponding proper name of said single-syllable language in said bilingual proper name list; and training said parsing statistic model base on the result of parsing that is determined as correct.

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.

The invention belongs to the technical field of named entities recognition, and discloses a Korean named entities recognition method based on a maximum entropy model and a neural network model. The method comprises the steps that a prefix tree dictionary is built, when any one combined noun template or any one proper noun template is matched in an input sentence, the combined noun template or the proper noun template are recognized into a target word; the target word is obtained in a target word selection module, the target word is searched in an entity dictionary, and when only one subclass is matched, the subclass serves as a tag of the target word; the maximum entropy model is adopted, and various linguistics information is utilized; a feedforward neural network model is constructed; adjacency words form an entity tag through a template selection rule. All data used in the method is extracted in a training corpus with tags and a field-independent entity dictionary, the data is very easily migrated to other application fields, and the performance cannot be reduced obviously.

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.

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 method for automatically analyzing the text of a document to generate verification questions to be administered to a user as a quiz for the purpose of verifying whether the user has read the document. Syntactic analysis is applied to statements (e.g. sentences) in the text to automatically generate various types of verification questions, including fill-in-the-blank, true / false, and multiple-choice questions. Nouns and proper nouns in a statement may be used to generate fill-in-the-blank questions; numerical values may be used to generate fill-in-the-blank, true / false and multiple-choice questions; and verbs, adjectives and adverbs may be used to generate true / false questions. The questions may be generated dynamically for each user, or generated once, stored and used for multiple users.

The claimed subject matter provides systems and / or methods that effectuate generation of alternative expressions or phrasings for short descriptions, proper nouns or places. The system can include devices that select and associate an item with a prompt, displays the selected item and then obscures the item with the prompt associated with the item, elicits a response from users to the prompt based on a motivational statement constructed to solicit an appropriate response from the user. The response elicited from the user and the item selected associated with one another and then persisted to storage media.

The invention provides a search text labeling method and device. The search text labeling method comprises the following steps of obtaining a candidate participle set of a text to be searched; reading preset information of words matched with each candidate participle in the candidate participle set from a semantic resource base; performing labeling on the candidate participles in the candidate participle set according to the preset information to obtain an initial labeling result; obtaining entity participles and / or proper noun participles in the initial labeling result; performing labeling on each entity participle and / or proper noun participle according to preset features to obtain a middle labeling result; generating a target labeling result according to a preset rule, association information of each candidate participle, the initial labeling result and the middle labeling result; labeling the search text according to the target labeling result, wherein the labeling result includes at least one target candidate participle and labeling information of each target candidate participle. By using the method and the device provided by the invention, the search text labeling precision can be effectively improved.

The present invention, in one embodiment, aids the user during composition of emails / letters / documents with assistance for correct gender usage. In one example application, first an automated user information look-up process is initiated over centralized databases using the proper names mentioned in the composition. Once matches are found, gender-related information is retrieved and the composer is assisted with gender recognition tools while composing gender-sensitive statements. When mismatches between proper nouns and the corresponding adjectives / pronouns are found, this method proceeds with highlighting or otherwise flagging the mismatching words. Upon right-clicking the highlighted words, the user is given suggestions for the most probably correct options. Examples of the idea explained in this invention can be incorporated in existing software / systems of email / document editor / composers.

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 a Uygur language part-of-speech tagging method. The method includes 1, formulating a Uygur language part-of-speech tagging set and a million-word Uygur language corpus; 2, selecting a method based on conditional random fields in primary tagging to build a Uygur language part-of-speech tagging model, wherein the method is flexible in feature extraction and high in accuracy; 3, building a correct tagging rule library, an unambiguous part-of-speech tagging dictionary and a proper noun dictionary, and building a primary part-of-speech tagging correction algorithm based on rules and dictionaries to further improve accuracy of primary part-of-speech tagging; 4, providing a part-of-speech tagging method based on stem extraction to further increase coverage rate of tagged words; 5, providing a secondary part-of-speech tagging statistical model to increase coverage rate and success rate of the tagged words; 6, tagging in secondary tagging through the unambiguous dictionary and the proper noun dictionary, and realizing secondary part-of-speech tagging with extremely high accuracy through stem extraction tagging and statistical model tagging. By the Uygur language part-of-speech tagging method, the problem of part-of-speech tagging of Uygur language is solved efficiently.

Disclosed are embodiments of a system and a method for detecting relationships described in unstructured text-based electronic documents. The system and method incorporate the use of an input file that contains one or more text patterns that represent particular relationships. The text patterns each include regular text expressions that describe the particular relationship and slots for the location of each entity in that relationship. Document(s) are selected by a user and scanned by a proper noun tagger that identifies and tags every occurrence of proper names within the document(s). Then, a pattern matcher scans the document(s) to match text patterns. If a text pattern is matched within a document a relationship detector extracts all pairs of proper names found in the slots for each matched text pattern. The output from the relationship detector includes the names for each entity in the relationship, the type of relationship, and the identity of the document and the location of the sentence describing the relationship in the document.

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 invention provides a method and a system for broadcasting polyphonic characters in the voice interaction process. The broadcasting method comprises the steps of acquiring voice information, and recognizing the voice information; forming feedback information; performing phonetic notation on the feedback information; broadcasting the feedback information; and releasing prior information. According to the invention, the acquired voice information is recognized and stored as text information and phoneme information, phonetic notation is performed on the feedback information by using the phoneme information, and then the feedback information is broadcast, so that broadcast accuracy of polyphonic characters in proper nouns can be effectively improved, and the broadcast effect of polyphonic characters is improved.

The invention discloses a named entity recognition method based on rules and an improved pre-training model. According to the method, on the basis of BERT pre-training, field data which are the same as downstream tasks are added to continue pre-training, and then fine adjustment is carried out on named entity recognition tasks; meanwhile, considering that part-of-speech can express attribute information of important words, additional feature information is added in the internal structure of the BERT model to enhance the recognition performance of the system; in the aspect of deep learning model construction, a convolutional neural network and a bidirectional recurrent neural network are integrated to carry out sentence-level feature extraction on a text, finally, an entity result recognized by the model is corrected in combination with rules, whether the entity length is smaller than a certain value or not is judged, and if the front is adjectives, a new entity is spliced to serve as the final entity word; according to the method, the named entity recognition accuracy can be improved, proper nouns in the textile fabric field can be effectively extracted, and compared with an existing method, the accuracy, the recall rate and the F1 value are greatly improved.

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.