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Record Nr. |
UNINA9910253872903321 |
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Autore |
Agarwal Basant |
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Titolo |
Prominent Feature Extraction for Sentiment Analysis [[electronic resource] /] / by Basant Agarwal, Namita Mittal |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (118 p.) |
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Collana |
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Socio-Affective Computing, , 2509-5706 |
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Disciplina |
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Soggetti |
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Neurosciences |
Natural language processing (Computer science) |
Computational linguistics |
Data mining |
Application software |
Natural Language Processing (NLP) |
Computational Linguistics |
Data Mining and Knowledge Discovery |
Information Systems Applications (incl. Internet) |
Computer Appl. in Social and Behavioral Sciences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Literature Survey -- Machine Learning Approach for Sentiment Analysis -- Semantic Parsing using Dependency Rules -- Sentiment Analysis using ConceptNet Ontology and Context Information -- Semantic Orientation based Approach for Sentiment Analysis -- Conclusions and FutureWork -- References -- Glossary -- Index. |
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Sommario/riassunto |
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The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract |
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