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Synopsis
Search is now going beyond looking for factual information and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present book addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. We present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm and a study that observes the viability of using a domain-specific lexicon to compute entities reputation.
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About the Author
Filipa Peleja always had a passion for data. During her PhD she explored topics such as sentiment analysis and recommendation systems. At Yahoo! Labs she could learn how to look at news articles and explore natural language techniques to work with these data. Later on, she had the opportunity to explore methods to enhance models used at Vodafone.
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- PublisherScholars' Press
- Publication date2017
- ISBN 10 3639511506
- ISBN 13 9783639511505
- BindingPaperback
- LanguageEnglish
- Number of pages180
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Learning Sentiment Lexicons with applications to Recommender Systems
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Scholars' Press Nov 2017, 2017
ISBN 10: 3639511506
ISBN 13: 9783639511505
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Search is now going beyond looking for factual information and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present book addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. We present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm and a study that observes the viability of using a domain-specific lexicon to compute entities reputation. 180 pp. Englisch. Seller Inventory # 9783639511505
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Learning Sentiment Lexicons with applications to Recommender Systems
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Search is now going beyond looking for factual information and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present book addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. We present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm and a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Seller Inventory # 9783639511505
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Learning Sentiment Lexicons with applications to Recommender Systems
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Peleja FilipaFilipa Peleja always had a passion for data. During her PhD she explored topics such as sentiment analysis and recommendation systems. At Yahoo! Labs she could learn how to look at news articles and explore natural langu. Seller Inventory # 385759179
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Learning Sentiment Lexicons with applications to Recommender Systems
Published by
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ISBN 10: 3639511506
ISBN 13: 9783639511505
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Search is now going beyond looking for factual information and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present book addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. We present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm and a study that observes the viability of using a domain-specific lexicon to compute entities reputation.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch. Seller Inventory # 9783639511505
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