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Bücher von Erik Cambria

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  • von Erik Cambria & Xiaoshi Zhong
    130,00 €

  • von Christoph Lange, Erik Cambria, Diego Reforgiato Recupero, usw.
    49,00 €

    This book constitutes the thoroughly refereed post conference proceedings of the first edition of the Semantic Web Evaluation Challenge, SemWebEval 2014, co-located with the 11th Extended Semantic Web conference, held in Anissaras, Crete, Greece, in May 2014. This book includes the descriptions of all methods and tools that competed at SemWebEval 2014, together with a detailed description of the tasks, evaluation procedures and datasets. The contributions are grouped in three areas: semantic publishing (sempub), concept-level sentiment analysis (ssa), and linked-data enabled recommender systems (recsys).

  • von Erik Cambria & Xiaoshi Zhong
    130,00 €

  • von Erik Cambria, Frank Xing & Roy Welsch
    94,00 €

  • von Amir Hussain, Erik Cambria & Soujanya Poria
    139,00 €

    Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer.

  • von Amir Hussain, Erik Cambria & Soujanya Poria
    140,00 €

    Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer.

  • - Techniques, Tools, and Applications
    von Amir Hussain, Erik Cambria & Ranjan Satapathy
    139,00 €

  • - A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
    von Amir Hussain & Erik Cambria
    94,00 - 96,00 €

    Sentic Computing

  • - Techniques, Tools, and Applications
    von Amir Hussain & Erik Cambria
    49,00 €

    In this book common sense computing techniques are further developed and applied to bridge the semantic gap between word-level natural language data and the concept-level opinions conveyed by these.

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