1. Articles in category: Semantic

    1-24 of 4119 1 2 3 4 ... 170 171 172 »
    1. Systems and methods for three-term semantic search

      Methods and systems for searching over a large corpus of data to discover relevant information artifacts based on similar content and/or relationships are disclosed. Improvements over simple keyword and phrase based searching over Internet scale data are shown. A search query may be modified or relaxed based on the search terms and a contextual relationship therebetween. The search results may be ranked based on both a data ranking corresponding to the data entries in the corpus and a query ranking corresponding to the search query and/or the modified or relaxed search query. In this manner, the accuracy and ...

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    2. Google SLING: An Open Source Natural Language Parser

      Google SLING: An Open Source Natural Language Parser

      Google SLING: An Open Source Natural Language Parser Written by Alex Armstrong Friday, 17 November 2017 Google Research has just released an open source project that might be of interest if you are into natural language processing. SLING is a combination of recurrent neural networks and frame based parsing. Natural language parsing is an important topic. You can get meaning from structure and parsing is how you get structure. It is important in processing both text and voice.

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    3. Identifying word collocations in natural language texts

      Systems and methods for identifying word collocations in natural language texts. An example method comprises: performing, by a computing device, semantico-syntactic analysis of a natural language text to produce a plurality of semantic structures; generating, in view of relationships defined by the semantic structures, a raw list of word combinations; producing a list of collocations by applying a heuristic filter to the raw list of word combinations; and using the list of collocations to perform a natural language processing operation.

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    4. Method and system for translating sentence between languages based on semantic structure of the sentence

      A method and computer system for translating sentences between languages from an intermediate language-independent semantic representation is provided. On the basis of comprehensive understanding about languages and semantics, exhaustive linguistic descriptions are used to analyze sentences, to build syntactic structures and language independent semantic structures and representations, and to synthesize one or more sentences in a natural or artificial language. A computer system is also provided to analyze and synthesize various linguistic structures and to perform translation of a wide spectrum of various sentence types. As result, a generalized data structure, such as a semantic structure, is generated from a ...

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    5. Translation and dictionary selection by context

      Methods are described for translation of one or more words in a source language into a target language based on context, history and meaning of portions of the source text. Translation may involve selection of electronic dictionaries when translating from a source language to one or more target languages. Various aspects of history, context and structures of words that reflect lexical, morphological, syntactic, and semantic properties facilitate selection or presentation of translations and options to a user. The methods are applicable to genre classification, topic detection, news analysis, authorship analysis, internet searches, and creating corpora for other tasks, etc.

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    6. Active knowledge guidance based on deep document analysis

      An approach is provided for an information handling system to present knowledge-based information. In the approach, a semantic analysis is performed on the document with the analysis resulting in various sets of semantic content. Each of the sets of semantic content corresponds to an area in the document. The areas of the document are visually highlighted using visual indicators that show the availability of the sets of semantic content to a user via a user interface. In response to a user selection, such as a selection using the user interface or a user specified configuration setting, a selected set of ...

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    7. Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      Elsevier Announces the Winner of the 2017 Semantic Web Challenge [November 13, 2017] Elsevier Announces the Winner of the 2017 Semantic Web Challenge VIENNA , November 13, 2017 /PRNewswire/ -- Elsevier , the information analytics business specializing in science and health, is pleased to announce the winner of the 2017 Semantic Web Challenge (SWC). The winner was announced at the International Semantic Web Conference held in Vienna, Austria in October.

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    8. Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      IBM Socrates was awarded the prestigious AI prize at International Semantic Web Conference PR Newswire VIENNA, November 13, 2017 VIENNA , November 13, 2017 /PRNewswire/ -- Elsevier , the information analytics business specializing in science and health, is pleased to announce the winner of the 2017 Semantic Web Challenge (SWC). The winner was announced at the International Semantic Web Conference held in Vienna, Austria in October. The challenge and allocated prize were sponsored by Elsevier.

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    9. Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      06:54 AM EST Elsevier Announces the Winner of the 2017 Semantic Web Challenge VIENNA , November 13, 2017 /PRNewswire/ -- Elsevier , the information analytics business specializing in science and health, is pleased to announce the winner of the 2017 Semantic Web Challenge (SWC). The winner was announced at the International Semantic Web Conference held in Vienna, Austria in October. The challenge and allocated prize were sponsored by Elsevier.

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    10. Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      Elsevier Announces the Winner of the 2017 Semantic Web Challenge IBM Socrates was awarded the prestigious AI prize at International Semantic Web Conference News provided by Share this article VIENNA , November Elsevier , the information analytics business specializing in science and health, is pleased to announce the winner of the 2017 Semantic Web Challenge (SWC). The winner was announced at the International Semantic Web Conference held in Vienna, Austria in October.

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    11. Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      Elsevier Announces the Winner of the 2017 Semantic Web Challenge IBM Socrates was awarded the prestigious AI prize at International Semantic Web Conference News provided by Share this article VIENNA , November Elsevier , the information analytics business specializing in science and health, is pleased to announce the winner of the 2017 Semantic Web Challenge (SWC). The winner was announced at the International Semantic Web Conference held in Vienna, Austria in October.

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    12. Elsevier Announces the Winner of the 2017 Semantic Web Challenge

      | 13.11.2017, 12:54 | 88 | 0 | 0 VIENNA , November 13, Elsevier , the information analytics business specializing in science and health, is pleased to announce the winner of the 2017 Semantic Web Challenge (SWC). The winner was announced at the International Semantic Web Conference held in Vienna, Austria in October. The challenge and allocated prize were sponsored by Elsevier.

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    13. Large scale biomedical texts classification: a kNN and an ESA-based approaches.

      Large scale biomedical texts classification: a kNN and an ESA-based approaches.

      Large scale biomedical texts classification: a kNN and an ESA-based approaches.

      J Biomed Semantics. 2016 Jun 16;7:40

      Authors: Dramé K, Mougin F, Diallo G

      Abstract BACKGROUND: With the large and increasing volume of textual data, automated methods for identifying significant topics to classify textual documents have received a growing interest. While many efforts have been made in this direction, it still remains a real challenge.

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      Mentions: ESA Random Forest
    14. Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.

      Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.

      J Med Internet Res. 2017 Nov 06;19(11):e380

      Authors: Lin C, Hsu CJ, Lou YS, Yeh SJ, Lee CC, Su SL, Chen HC

      Abstract BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance.

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    15. Standard exact clause detection

      Embodiments relate to a system and a method for identifying, from contractual documents, (i) standard exact clauses matching clause examples and (ii) non-standard clauses semantically related to but not matching the clause examples. A standard feature data set comprising standard exact clauses matching clause examples is obtained. In addition, a mirror feature data set comprising semantically related clauses of the clause examples is obtained using semantic language analysis, where the mirror feature data set encompasses the standard feature data set. Non-standard clauses are obtained by extracting a difference between the mirror feature data set and the standard exact feature data ...

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    16. Method of notifying function identification information and communication system

      There is disclosed a notification method in a communication system of notifying specific multifunctionality information between terminal stations. An expansion code is generated from both a user input code and a function identification code corresponding to a specific function. A transmission frame including the expansion code is also generated and transmitted to at least one of the terminal stations.

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    17. Anaphora resolution for semantic tagging

      A semantic tagging method may add context to a sentence in order to increase search efficiency. Regardless of an author's writing style, translating semantic concepts into tags may increase search efficiency. Automatic semantic tagging of documents may allow semantic search and reasoning. Text for semantic tagging may include an email, a website chat room, an internet forum, or a text message. Additional texts may include aggregating general consensus of an emailed topic across multiple emails, whether in the same email chain or separate emails. To increase search efficiency, the analysis of prior communications within the body of text may ...

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    18. Interspecies gene function prediction using semantic similarity.

      Interspecies gene function prediction using semantic similarity.

      Interspecies gene function prediction using semantic similarity.

      BMC Syst Biol. 2016 Dec 23;10(Suppl 4):121

      Authors: Yu G, Luo W, Fu G, Wang J

      Abstract BACKGROUND: Gene Ontology (GO) is a collaborative project that maintains and develops controlled vocabulary (or terms) to describe the molecular function, biological roles and cellular location of gene products in a hierarchical ontology. GO also provides GO annotations that associate genes with GO terms.

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      Mentions: Gene Ontology Mouse
    19. Querying EHRs with a Semantic and Entity-Oriented Query Language.

      Querying EHRs with a Semantic and Entity-Oriented Query Language.

      Stud Health Technol Inform. 2017;235:121-125

      Authors: Lelong R, Soualmia L, Dahamna B, Griffon N, Darmoni SJ

      Abstract While the digitization of medical documents has greatly expanded during the past decade, health information retrieval has become a great challenge to address many issues in medical research.

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    20. NTENT Implements Applied Data Science to Identify User Intention and Increase Relevance

      NTENT Implements Applied Data Science to Identify User Intention and Increase Relevance [October 17, 2017] NTENT Implements Applied Data Science to Identify User Intention and Increase Relevance NTENT announced today a multiphase approach to understanding language that uses Applied Data Science to sift through data collected worldwide, as a means to measure user intention and provide relevant solutions.

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    21. NTENT Implements Applied Data Science to Identify User Intention and Increase Relevance

      NTENT Implements Applied Data Science to Identify User Intention and Increase Relevance

      NEW YORK- NTENT announced today a multiphase approach to understanding language that uses Applied Data Science to sift through data collected worldwide, as a means to measure user intention and provide relevant solutions. Applied Data Science refers to the collection and collation of information derived from a blend of data mining, data processing, predictive analytics and machine learning.

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    22. Semantic natural language vector space

      Techniques for image captioning with word vector representations are described. In implementations, instead of outputting results of caption analysis directly, the framework is adapted to output points in a semantic word vector space. These word vector representations reflect distance values in the context of the semantic word vector space. In this approach, words are mapped into a vector space and the results of caption analysis are expressed as points in the vector space that capture semantics between words. In the vector space, similar concepts with have small distance values. The word vectors are not tied to particular words or a ...

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    1-24 of 4119 1 2 3 4 ... 170 171 172 »
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