1. Articles in category: Semantic

    25-48 of 4101 « 1 2 3 4 5 ... 169 170 171 »
    1. An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining.

      An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining.

      An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining.

      IEEE/ACM Trans Comput Biol Bioinform. 2016 Jul-Aug;13(4):634-42

      Authors: Jiang Z, Li L, Huang D

      Abstract In biomedical text mining tasks, distributed word representation has succeeded in capturing semantic regularities, but most of them are shallow-window based models, which are not sufficient for expressing the meaning of words.

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      Mentions: Li L
    2. Extracting Biomedical Event with Dual Decomposition Integrating Word Embeddings.

      Extracting Biomedical Event with Dual Decomposition Integrating Word Embeddings.

      Extracting Biomedical Event with Dual Decomposition Integrating Word Embeddings.

      IEEE/ACM Trans Comput Biol Bioinform. 2016 Jul-Aug;13(4):669-77

      Authors: Li L, Liu S, Qin M, Wang Y, Huang D

      Abstract Extracting biomedical event from literatures has attracted much attention recently. By now, most of the state-of-the-art systems have been based on pipelines which suffer from cascading errors, and the words encoded by one-hot are unable to represent the semantic information.

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      Mentions: Li L Wang Y
    3. Method for deducing entity relationships across corpora using cluster based dictionary vocabulary lexicon

      An approach is provided for identifying entity relationships based on word classifications extracted from business documents stored in a plurality of corpora. In the approach, performed by an information handling system, a plurality of cluster classifications are identified for the business documents so that entity information from the business documents can be classified or assigned to the cluster classifications, such as by performing natural language processing (NLP) analysis of the business documents. The approach applies semantic analysis to identify and score entity relationships between the entity information classified in the cluster classifications, and based on the scored entity relationships, cluster ...

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    4. Visual Exploration of Semantic Relationships in Neural Word Embeddings.

      Visual Exploration of Semantic Relationships in Neural Word Embeddings.

      Visual Exploration of Semantic Relationships in Neural Word Embeddings.

      IEEE Trans Vis Comput Graph. 2017 Aug 29;:

      Authors: Liu S, Bremer PT, Thiagarajan JJ, Srikumar V, Wang B, Livnat Y, Pascucci V

      Abstract Constructing distributed representations for words through neural language models and using the resulting vector spaces for analysis has become a crucial component of natural language processing (NLP).

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      Mentions: NLP PCA
    5. Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features.

      Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features.

      AMIA Annu Symp Proc. 2016;2016:1283-1292

      Authors: Zhang Y, Jiang M, Wang J, Xu H

      Abstract Semantic role labeling (SRL), which extracts shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding clinical narratives.

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    6. Semantic disambiguation using a statistical analysis

      A text containing a word is received by a computing device. The word is compared to inventory words in a sense inventory. The sense inventory comprises at least one inventory word and at least one concept corresponding to the at least one inventory word. Upon matching the word to an inventory word in the sense inventory, a concept for the word is identified by comparing each concept related to the inventory word to the word. The concept is assigned the word.

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    7. Information handling system and computer program product for deducing entity relationships across corpora using cluster based dictionary vocabulary lexicon

      An approach is provided for identifying entity relationships based on word classifications extracted from business documents stored in a plurality of corpora. In the approach, performed by an information handling system, a plurality of cluster classifications are identified for the business documents so that entity information from the business documents can be classified or assigned to the cluster classifications, such as by performing natural language processing (NLP) analysis of the business documents. The approach applies semantic analysis to identify and score entity relationships between the entity information classified in the cluster classifications, and based on the scored entity relationships, cluster ...

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    8. Ontology mapper

      Systems, methods and computer-readable media are provided for facilitating patient health care by providing discovery, validation, and quality assurance of nomenclatural linkages between pairs of terms or combinations of terms in databases extant on multiple different health information systems that do not share a set of unified codesets, nomenclatures, or ontologies, or that may in part rely upon unstructured free-text narrative content instead of codes or standardized tags. Embodiments discover semantic structures existing naturally in documents and records, including relationships of synonymy and polysemy between terms arising from disparate processes, and maintained by different information systems. In some embodiments, this ...

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    9. System and method for transforming inter-component communications through semantic interpretation

      A system and method for transforming inter-communications in a computing platform that includes establishing platform policies; isolating components of a platform; channeling communications of a component through a semantic pipeline; progressively processing a communication through stages of the semantic pipeline; and delivering the processed communication to the destination component in accordance with the semantic pipeline.

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    10. 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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    11. 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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    12. 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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    13. Theory behind Image Compression and Semantic Search

      Theory behind Image Compression and Semantic Search

      Show related SlideShares at end WordPress Shortcode Theory behind Image Compression and Semantic Search 93 views Published on Jun 27, 2017 Singular Value Decomposition (SVD) is a matrix decomposition technique developed during the 18th century and has been in use ever since. SVD has applications in several areas including image processing, natural language processing (NLP), genomics, and data compression.

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    14. 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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    15. 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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    16. 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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    25-48 of 4101 « 1 2 3 4 5 ... 169 170 171 »
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