10490results about "Semantic tool creation" patented technology

In a pay-for-placement search system, the system makes search term recommendations to advertisers managing their accounts in one or more of two ways. A first technique involves looking for good search terms directly on an advertiser's web site. A second technique involves comparing an advertiser to other, similar advertisers and recommending the search terms the other advertisers have chosen. The first technique is called spidering and the second technique is called collaborative filtering. In the preferred embodiment, the output of the spidering step is used as input to the collaborative filtering step. The final output of search terms from both steps is then interleaved in a natural way.

Techniques for factoring one or more source graphs into a composite graph containing nodes representing analogous elements of the source graphs and a variability graph containing nodes representing differences in the source graphs. The composite graph is made by taking analogous input trees from the source graphs and traversing the trees from top to bottom looking for nodes in each tree at each level that are analogous to the nodes at that level in the other input trees. The sets of analogous nodes are found by first automatically correlating the nodes in the level currently being examined. Correlation may, for example, be based on similar values of a property of the nodes being correlated. Representations of the sets of correlated nodes are then displayed to a user, who indicates which sets of correlated nodes are in fact analogous. The user may also indicate that the nodes in a set of correlated nodes are not analogous or that nodes that were found by the automatic correlation not to be autonomous are in fact. The analogous nodes are allocated to a corresponding node at a corresponding level in the composite graph; the other nodes are allocated to a set of anomalous nodes. One application for the techniques is managing graphs which are models of catalogs of items.

Controls are provided for a web server to generate client side markups that include recognition and / or audible prompting. The controls comprise elements of a dialog such as a question, answer, confirmation, command or statement. A module forms a dialog by making use of the information carried in the controls. The dialog follows a selected order of prompting and receiving input from a user as related to the order of the controls, and departs from the selected order as a function of responses from the user. The speech controls are adapted such that elements of the speech controls can be combined or re-used.

A computer-implemented method is provided for searching documents containing complex bodies of knowledge, such as patents and research papers. The computer-implemented method and related hardware and software provides methodology to interpret the intent of the searcher (the meaning of the searcher's query) into a MetaLanguage, including but not limited to the use of Fundamental Nature Attributes, Fundamental Action Attributes and Weighting of these attributes as it pertains to the intent of the searcher. The invention relates to semantic based searches. The same methodology that is used on the searcher's query is also used to mine and store the existing databases of patents and research papers into databases of MetaLanguage for the purpose of producing search results that better match search inquiries.

An apparatus for providing a control input signal for an industrial process or technical system having one or more controllable elements includes elements for generating a semantic space for a text corpus, and elements for generating a norm from one or more reference words or texts, the or each reference word or text being associated with a defined respective value on a scale, and the norm being calculated as a reference point or set of reference points in the semantic space for the or each reference word or text with its associated respective scale value. Elements for reading at least one target word included in the text corpus, elements for predicting a value of a variable associated with the target word based on the semantic space and the norm, and elements for providing the predicted value in a control input signal to the industrial process or technical system. A method for predicting a value of a variable associated with a target word is also disclosed together with an associated system and computer readable medium.

A system and methods are provided for runtime spelling analysis and correction in a computing system. Misspelled entries or input text is automatically corrected turning the misspelled entries or input text into valid entries or text. The words used for spell checking and correction may be collected through multiple channels or from multiple sources, including words commonly found on the Web, and in users' entries or input text, as well as words from a standard language lexicon, all of which may be in one or more languages. The word(s) are automatically corrected only when there is a very high confidence that the correction is desirable. In various embodiments, the system implements a plurality of mechanisms with which the user can override the correction if invoked.

A method and system organize and retrieve information using taxonomies, a document classifier, and an autocontextualizer. Documents (or other knowledge containers) in an organization and retrieval subsystem may be manually or automatically classified into taxonomies. Documents are transformed from clear text into a structured record. Automatically constructed indexes help identify when the structured record is an appropriate response to a query. An automatic term extractor creates a list of terms indicative of the documents' subject matter. A subject matter expert identifies the terms relevant to the taxonomies. A term analysis system assigns the relevant terms to one or more taxonomies, and a suitable algorithm is then used to determine the relatedness between each list of terms and its associated taxonomy. The system then clusters documents for each taxonomy in accordance with the weights ascribed to the terms in the taxonomy's list and a directed acyclic graph (DAG) structure is created.

Systems and processes for detecting an event within natural language are provided. In one example of a process, unstructured natural language information may be received from at least one user. The presence of event information in the unstructured natural language information may be determined. In accordance with a determination that event information is present within the unstructured natural language information, a pseudo-event entry associated with that event information may be generated.

In a pay-for-placement search system, the system makes search term recommendations to advertisers managing their accounts in one or more of two ways. A first technique involves looking for good search terms directly on an advertiser's web site. A second technique involves comparing an advertiser to other, similar advertisers and recommending the search terms the other advertisers have chosen. The first technique is called spidering and the second technique is called collaborative filtering. In the preferred embodiment, the output of the spidering step is used as input to the collaborative filtering step. The final output of search terms from both steps is then interleaved in a natural way.

Methods and devices to externally create a restriction on the stomach are described. The devices are contoured to fit the stomach and can be further anchored to the stomach. The degree of deployment of the extragastric restriction device is controllable after implantation. Specialized wires, catheters, ports, and trocars specific for placement of extragastric restriction devices are presented. Systems are described in which adjustability of the devices is provided along with sensing and actuating ability.

The invention provides a question and answer method based on a knowledge map. The question and answer method based on a knowledge map provided in the invention is realized by subject entity matching,relationship matching and answer determination. The subject entity matching mainly comprises naming entity identification and entity linking. The naming entity identification is aimed at identifying naming entities such as names of people, names of places, and names of organizations in natural language questions q. The entity linking corresponds the identified naming entity to a certain entity inthe knowledge base, that is, finding out an entity s in triples; Relationship matching is to understand the semantics expressed by question q through natural language understanding technology, and match the relationship p in the triples (s, p, o) in the search space in order to determine the semantics of the question and its corresponding relationship with the knowledge base. The candidate subjectentity is obtained through entity identification and entity linking, and the relationship matching can obtain the candidate relationship, thereby obtaining several candidate triples; the answer determination is to rank the candidate triples according to entity recognition score, relationship match score, etc. to determine the final answer.

The invention discloses a Chinese natural language interrogative sentence semantization knowledge base automatic question-answering method. The method includes the following steps that Chinese natural language processing is performed on a fact type question input by a user, word segmentation, part-of-speech tagging and identification and expanding of a named entity are achieved, and a semantic dependency tree is generated; a generalization template and a semantic analysis technology are used for acquiring time, space, a fact entity, a fact object and the like in an interrogative sentence, then semantic processing is performed, composition element attributes relevant to all events in the interrogative sentence and values of the attributes are extracted, a plurality of 'attribute-value' pairs are generated, to-be-answered elements are substituted by interrogatives, and a complex fact triple set is formed; after a triple where a to-be-answered part is located is combined with other relevant fact triple sets to form knowledge base query with conditional constraints, and query matching based on similarity calculation is performed in a knowledge base, a result is extracted from the knowledge base, and a final answer is obtained. Fast and accurate query response to the knowledge base is achieved.

Methods and devices to externally create a restriction on the stomach are described. In some embodiments, the devices are contoured to fit the stomach and can be further anchored to the stomach. In further embodiments, the degree of deployment of the extragastric restriction device is controllable after implantation. In other embodiments, specialized wires, catheters, ports, and trocars specific for placement of extragastric restriction devices are presented. In still further embodiments, systems are described in which adjustability of the devices is provided along with sensing and actuating ability.

Techniques are provided for semantic matching. A semantic index is created for one or more schemas, wherein each of the one or more schemas includes one or more word attributes, and wherein each of the one or more word attributes includes one or more tokens, wherein the semantic index identifies one or more keys and one or more values for each key, wherein each value specifies one of the one or more schemas, a word attribute from the specified schema, and a token of the specified word attribute, and wherein the specified token is a synonym of the key. For a source word attribute from one of the one or more schemas, the source word attribute is used as a key to index the semantic index to identify one or more matching word attributes.

A system, method, and computer program product for natural language understanding, including forming pairs of words and / or phrases in independent phrases in a sentence, wherein each word and / or phrase is paired with every other word and / or phrase; determining meanings for the words and / or phrases; comparing the meanings of each word and / or phrase with each meaning of the other word and / or phrase in the pair; selecting the pairs with the best relationships; combining highly-related pairs with other highly-related pairs to form longer groups of words; exchanging word meanings for the longer groups with word meanings having a weaker relationship to determine if the exchanged word meanings provide an overall stronger relationship; and forming longer and longer groups until the sentence is understood.

The present disclosure provides a semantic understanding based emoji input method and device, and relates to the input method technology field. The method includes: obtaining a text content according to an input sequence; performing word segmentation on the text content, and extracting text features based on the word segmentation result; constructing an input vector using the text features, performing classification using an emotion classification model to determine an emotion label of the text content; based on a correspondence relationship between the emotion label and emojis of various themes, respectively obtaining an emoji corresponding to the emotion label from each of the various themes; sorting the obtained emojis of the various themes, and displaying the sorted emojis as candidate options in a client. The disclosed invention facilitates users to input an emoji, enhances emoji input efficiency, and provides users with rich and wide scope of emoji resources.

Disclosed systems, methods, and computer readable media can detect an association between semantic entities and generate semantic information between entities. For example, semantic entities and associated semantic collections present in knowledge bases can be identified. A time period can be determined and divided into time slices. For each time slice, word embeddings for the identified semantic entities can be generated; a first semantic association strength between a first semantic entity input and a second semantic entity input can be determined; and a second semantic association strength between the first semantic entity input and semantic entities associated with a semantic collection that is associated with the second semantic entity can be determined. An output can be provided based on the first and second semantic association strengths.

Related free-text documents, a corpus, are used to empirically derive a semantic knowledge base through a method in which documents are segmented into unique sentences, and then used to define sentential propositions which are arranged in a knowledge hierarchy. The method takes compound natural language sentences and transforms them to simple sentences by a process that is a part of the invention. A knowledge editor enables a domain expert using the methods of the invention to map the sentences in the corpus to sentential proposition(s). The resulting knowledge base can be used to semantically analyze documents in data mining and decision support applications, and can assist word processors or speech recognition devices. The invention is illustrated in connection with radiology reports, but it has wide applicability.

A system, method, and computer program product for domain-independent natural language understanding, including at least one of forming pairs of words and / or phrases in a sentence, wherein each word and / or phrase is paired with every other word and / or phrase; determining meanings for the words and / or phrases; assigning numeric codes that uniquely identify semantic concepts to those word and / or phrase meanings; comparing the numeric code of each word and / or phrase with each numeric code of the other word and / or phrase in the pair; selecting the pairs with the best relationships; combining highly-related pairs with other highly-related pairs to form longer groups of words; exchanging numeric codes for the longer groups with numeric codes having a weaker relationship to determine if the exchanged numeric codes provide an overall stronger relationship; and forming longer and longer groups until the sentence is understood.

Determining a semantic relationship is disclosed. Source content is received. Cluster analysis is performed at least in part by using at least a portion of the source content. At least a portion of a result of the cluster analysis is used to determine the semantic relationship between two or more content elements comprising the source content.

A semantic discovery and exploration system is disclosed where an environment enabling a developer or user to uncover, navigate, and organize semantic patterns and structures in a document collection with or without the aid of structured knowledge. The semantic discovery and exploration system provides techniques for searching document collections, categorizing documents, inducing lists of related concepts, and identifying clusters of related terms and documents. This system operates both without and with infusions of structured knowledge such as gazetteers, thesauruses, taxonomies and ontologies. System performance improves when structured knowledge is incorporated. The semantic discovery and exploration system may be used as a first step in developing an information extraction system such as to categorize or cluster documents in a particular domain or to develop gazetteers and as a part of a deployed run-time information extraction system. It may also be used as standalone utility for searching, navigating, and organizing document collections and structured knowledge bases such as dictionaries or domain-specific reference works.

A system and methods for matching between search requests and relevant data (web pages, online documents, essays, online text in general, images, video, footage etc.). The system comprises three components that can work separately or together and can be integrated with other search engine methods in order to further improve the relevancy of search results. The system can find similarity between different document and measure the distance (in similarity) between documents. The three components are: Context based understanding, comprising putting the documents in the context of aspects of the human knowledge external to the documents, Partial Sentence analysis and 100 percentage points to keyword / tag sets.

Disclosed herein are embodiments of systems, devices, and methods automated document analysis and processing using machine learning techniques. In one embodiment, systems and methods are disclosed for automatically classifying documents. In another embodiment, systems and methods are disclosed for identifying new tags for untagged documents. In another embodiment, systems and methods are disclosed for identifying documents related to a target document.

The invention discloses a Chinese event extraction method. The method comprises the following steps of: 1) carrying out entity identification on a to-be-extracted Chinese text, taking identified entities as candidate words of event elements, labeling the Chinese text word by word, and identifying an event triggering word in the Chinese text and event types described by the Chinese text by combing a labeling mode according to the labeling result; 2) inputting the Chinese text, the candidate words of the event elements, the event triggering word and the event types into a classification model, and judging whether each candidate word is a real event element or not; and 3) obtaining a whole event structure according to the obtained event elements, the event triggering word and the event types so as to complete event extraction. According to the method disclosed by the invention, the problem that the event triggering word is not completely matched with the words in the text in the Chinese event extraction is solved, and the correctness of the Chinese event extraction is improved.

Tools and methods for schema matching that generate schema graphs, populate match matrices and display the schema graphs and the match matrices. These tools and methods characterize potential matches between disparate schemata in terms of both a strength of evidence indicating the potential match and an amount of evidence indicating the potential match. A number of match voters generate a set of match scores for each potential match, and these match scores are combined by a vote merger to form a single confidence value for each potential match. A number of filters display the confidence value for each potential match as a link on a graphical user interface. Machine-learning techniques may be employed to adaptively determine confidence values based on previously established matches.

The invention discloses an NLP-based electronic medical record data quality management method. Electronic medical record operation and quality management operation are integrated in an intelligent mode, the quality requirements of the electronic medical record are converted to quality management knowledge, in match with electronic medical record ontology knowledge, a method of interaction operation of manual audit and intelligent audit is adopted, and quality check is carried out. The method particularly comprises the following steps of (1) preparation, (2) quality problem recognition, (3) quality problem evaluation, (4) quality problem monitoring and (5) quality report generation. Automatic and intelligent electronic medical record quality control is realized by introducing technologies such as an ontology and an NLP, the shortcomings of the existing manual quality audit are overcome, quality check is carried out on the electronic medical record in match with the ontology knowledge, the electronic medical record quality problem is thus found out, the efficiency is improved, and the generated result is more professional, accurate, objective, fair and just.

The invention relates to a construction method of a knowledge map question answering system in the field of electric power communication based on deep learning, which comprises the following steps: Step 1, semantic analysis, that is, preprocessing a question q put forward by a user in a natural language, extracting a keyword of a user inquiry, a focus of a query sentence and the like as an entityw of a question sentence from the question q; Step 2: semantic expression, namely, vectorization of the natural language question after preprocessing, and vectorization of the candidate set of answera, are used to calculate the matching degree of the question q and the answer a; and Step 3, the answer a most matched with the question q and most accurate is found through the method of semantic matching degree calculation, query and inference, so that the score S (q, a) of the question-answer pair (q, a) is the highest. The invention studies the feasibility of the question answering system constructed by the knowledge map in the field of communication of the State Grid.