1. Articles in category: Semantic

    1-24 of 4062 1 2 3 4 ... 168 169 170 »
    1. Natural language semantic search system and method using weighted global semantic representations

      Semantic Search Engine using Lexical Functions and Meaning-Text Criteria, that outputs a response (R) as the result of a semantic matching process consisting in comparing a natural language query (Q) with a plurality of contents (C), formed of phrases or expressions obtained from a contents' database (6), and selecting the response (R) as being the contents corresponding to the comparison having a best semantic matching degree. It involves the transformation of the contents (C) and the query in individual words or groups of tokenized words (W1, W2), which are transformed in its turn into semantic representations (LSC1, LSC2) thereof, by ...

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    2. Estimating the average need of semantic knowledge from distributional semantic models.

      Estimating the average need of semantic knowledge from distributional semantic models.

      Estimating the average need of semantic knowledge from distributional semantic models.

      Mem Cognit. 2017 Jul 13;:

      Authors: Hollis G

      Abstract Continuous bag of words (CBOW) and skip-gram are two recently developed models of lexical semantics (Mikolov, Chen, Corrado, & Dean, Advances in Neural Information Processing Systems, 26, 3111-3119, 2013).

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    3. A Semantic Sentence Similarity Estimation System For The Biomedical Domain

      Advanced Search Abstract Motivation: The amount of information available in textual format is rapidly increasing in the biomedical domain. Therefore, natural language processing (NLP) applications are becoming increasingly important to facilitate the retrieval and analysis of these data. Computing the semantic similarity between sentences is an important component in many NLP tasks including text retrieval and summarization.

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    4. Quasi natural language man-machine conversation device base on semantic logic

      The presented is a tool and method for language presentation, browsing, editing, translation and communication based on Semantic Web, to be utilized as interface for collaborating software products and services or human-machine interaction. The conceptual system is extended to further include such objects as language components, sentence patterns or syntax rules, to get solutions for semantic logic representation devices, language presentation devices, semantic-language converting devices, the registry and delegation system, in forming a language-component-based system for browsing, editing, conversion and communication. It is always allowed to bring need-based control over the conceptual system and the registry with their scope and ...

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    5. Question answering system-based generation of distractors using machine learning

      Generating distractors for text-based MCT items. An MCT item stem is received. The stem is transmitted to a QA system and a plurality of candidate answers related to the stem is received from the QA system. Incorrect answers in the plurality of candidate answers are identified. Textual features are extracted from the stem. A set of semantic criteria associated with the extracted textual features is generated. Based on the generated semantic criteria, a subset of the incorrect candidate answers is selected.

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    6. Text to image translation

      Techniques are described for online real time text to image translation suitable for virtually any submitted query. Semantic classes and associated analogous items for each of the semantic classes are determined for the submitted query. One or more requests are formulated that are associated with analogous items. The requests are used to obtain web based images and associated surrounding text. The web based images are used to obtain associated near-duplicate images. The surrounding text of images is analyzed to create high-quality text associated with each semantic class of the submitted query. One or more query dependent classifiers are trained online ...

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    7. Consensus search device and method

      A consensus search device is provided, which includes a semantic data indexing unit configured to divide text data of an electronic document written about at least one object into segments, to extract at least one semantic descriptor from the each segmented text data, and to generate a semantic data index matching each of the extracted semantic descriptor to the object and the each segmented text data. The consensus search device also includes a semantic searching unit configured to retrieve an object related to a query, based on the semantic data index. The text data is divided into the segments by ...

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    8. What is Latent Semantic Analysis (LSI Indexing)?

      Join Date: Oct 2016 Posts: 535 Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. To view links or images in signatures your post count must be 10 or greater. You currently have 0 posts. | To view links or images in signatures your post count must be 10 or greater.

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    9. Apparatus, system and method for application-specific and customizable semantic similarity measurement

      The present invention relates to an apparatus system and method for creating a customizable and application-specific semantic similarity utility that uses a single similarity measuring algorithm with data from broad-coverage structured lexical knowledge bases (dictionaries and thesauri) and corpora (document collections). More specifically the invention includes the use of data from custom or application-specific structured lexical knowledge bases and corpora and semantic mappings from variant expressions to their canonical forms. The invention uses a combination of technologies to simplify the development of a generic semantic similarity utility; and minimize the effort and complexity of customizing the generic utility for a ...

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    10. Semantic processing of content for product identification

      This disclosure describes systems, methods, and computer-readable media related to semantic processing of content for product identification. Content may be received from a user device. The content may be processed based at least in part on one or more content filters. At least a portion of the processed content may be analyzed with named-entity recognition to identify one or more product references. A confidence score associated with each of the one or more product references may be calculated. Data associated with the one or more product references may be obtained. The data associated with the one or more product references ...

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    11. RysannMD: A Biomedical Semantic Annotator Balancing Speed and Accuracy.

      RysannMD: A Biomedical Semantic Annotator Balancing Speed and Accuracy.

      RysannMD: A Biomedical Semantic Annotator Balancing Speed and Accuracy.

      J Biomed Inform. 2017 May 25;:

      Authors: Cuzzola J, Jovanovic J, Bagheri E

      Abstract Recently, both researchers and practitioners have explored the possibility of semantically annotating large and continuously evolving collections of biomedical texts such as research papers, medical reports, and physician notes in order to enable their efficient and effective management and use in clinical practice or research laboratories. Such annotations can be automatically generated by biomedical semantic annotators - tools that are specifically designed for detecting and disambiguating biomedical concepts mentioned in text. The biomedical community has already presented several ...

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      Mentions: Coder
    12. Semantic similarity evaluation method, apparatus, and system

      A semantic similarity evaluation method includes performing word vectorization processing separately on words in a first sentence and a word in a second sentence to obtain a first word vector and a second word vector; performing, in a preset word vector compression order, compression coding processing on the first word vector according to a first compression coding parameter to obtain a first statement vector; performing, in the preset word vector compression order, compression coding processing on the second word vector according to a second compression coding parameter to obtain a second statement vector; and determining a vector distance between the ...

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    13. Semantic query language

      Various technologies described herein pertain to executing a mixed query to search a database retained in a data repository. The mixed query includes a regular expression, which is a pattern of elements, and a semantic constraint. The elements in the regular expression include a first wildcard, where the semantic constraint restricts a meaning of the first wildcard. Moreover, the elements in the regular expression include explicit lexical constraint(s) and/or disparate wildcard(s). For instance, semantic constraint(s) can restrict meaning(s) of the disparate wildcard(s). The mixed query is executed to retrieve results that match the pattern ...

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    14. Machine learning and training a computer-implemented neural network to retrieve semantically equivalent questions using hybrid in-memory representations

      Determining semantically equivalent text or questions using hybrid representations based on neural network learning. Weighted bag-of-words and convolutional neural networks (CNN) based distributed vector representations of questions or text may be generated to compute the semantic similarity between questions or text. Weighted bag-of-words and CNN based distributed vector representations may be jointly used to compute the semantic similarity. A pair-wise ranking loss function trains neural network. In one embodiment, the parameters of the system are trained by minimizing a pair-wise ranking loss function over a training set using stochastic gradient descent (SGD).

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      Mentions: CNN
    15. System for semantic interpretation

      A semantic database is generated to provide answers to questions by users. Text processors can receive text from text sources, and can convert the text into intermediate logical statements. The text processors can then convert these statements into unambiguous semantic representations. A semantic database connected to the text processors can store the semantic representations. Query processors connected to the semantic database can receive a question from a computing device operated by a user, and can convert the question into intermediate logical subqueries. The query processors can then use a disambiguation table to generate unambiguous semantic subqueries from these intermediate logical ...

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    16. Semantic Technologies for Re-Use of Clinical Routine Data.

      Semantic Technologies for Re-Use of Clinical Routine Data.

      Semantic Technologies for Re-Use of Clinical Routine Data.

      Stud Health Technol Inform. 2017;236:24-31

      Authors: Kreuzthaler M, Martínez-Costa C, Kaiser P, Schulz S

      Abstract Routine patient data in electronic patient records are only partly structured, and an even smaller segment is coded, mainly for administrative purposes. Large parts are only available as free text.

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    17. Annotating Logical Forms for EHR Questions.

      Annotating Logical Forms for EHR Questions.

      Annotating Logical Forms for EHR Questions.

      LREC Int Conf Lang Resour Eval. 2016 May;2016:3772-3778

      Authors: Roberts K, Demner-Fushman D

      Abstract This paper discusses the creation of a semantically annotated corpus of questions about patient data in electronic health records (EHRs). The goal is to provide the training data necessary for semantic parsers to automatically convert EHR questions into a structured query.

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      Mentions: NLP EHR Roberts K
    18. Converting Text to Structured Models of Healthcare Services.

      Converting Text to Structured Models of Healthcare Services.

      Converting Text to Structured Models of Healthcare Services.

      Stud Health Technol Inform. 2016;226:123-6

      Authors: Despotou G, Matragkas N, Arvanitis TN

      Abstract The paper presents a concise method for transforming textual representations of healthcare services, to a structured, semantically unambiguous modelling language. The method is designed based on literature, as well as trial and error by the authors, using text descriptions of healthcare services.

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    19. Adjustment of document relationship graphs

      Provided is a process of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising obtaining a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; obtaining an n-gram indicating that edge weights affected by the n-gram are to be increased or decreased; expanding the n-gram to produce a set of expansion n-grams; adjusting edge weights ...

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    20. On-page SEO in 2017: Optimizing for RankBrain & Semantic Search -

      2.3K #growthhacks #localseo #seo We've been hearing about "semantic search" since Google's Hummingbird update back in 2013. Now, Google's leveraging it in numerous ways: the Knowledge Graph, RankBrain, LSI, natural language processing algorithms... In today's post on 5 major aspects of semantic search (and their implications for SEO), I'm doing my best to explain how semantic search works and what you need (and don't need!) to change in your strategy to grow rankings in 2017.

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    21. Exhaustive automatic processing of textual information

      A system for natural language processing is provided. A first natural language processing program may be constructed using language-independent semantic descriptions, and language-dependent morphological descriptions, lexical descriptions, and syntactic descriptions of one or more target languages. The natural language processing program may include any of machine translation, fact extraction, semantic indexing, semantic search, sentiment analysis, document classification, summarization, big data analysis, or another program. Additional sets of natural language processing programs may be constructed.

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    1-24 of 4062 1 2 3 4 ... 168 169 170 »
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