Computing attitude affect text (21 résultats)
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Computing Attitude And Affect in Text : Theory And Applications
Shanahan, James G. (EDT); Qu, Yan (EDT); Wiebe, Janyce M. (EDT)
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Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series, 20)
Shanahan, James G. [Editor]; Qu, Yan [Editor]; Wiebe, Janyce [Editor];
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hardcover. Etat : New. In shrink wrap. Looks like an interesting title.
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Computing Attitude And Affect in Text : Theory And Applications
Shanahan, James G. (EDT); Qu, Yan (EDT); Wiebe, Janyce M. (EDT)
Langue : anglais
Edité par Springer, 2005
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Computing Attitude And Affect in Text : Theory And Applications
Shanahan, James G. (EDT); Qu, Yan (EDT); Wiebe, Janyce M. (EDT)
Langue : anglais
Edité par Springer, 2005
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Computing Attitude And Affect in Text : Theory And Applications
Shanahan, James G. (EDT); Qu, Yan (EDT); Wiebe, Janyce M. (EDT)
Langue : anglais
Edité par Springer, 2005
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Autres imagesLangue : anglais
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Taschenbuch. Etat : Neu. Computing Attitude and Affect in Text: Theory and Applications | James G. Shanahan (u. a.) | Taschenbuch | The Information Retrieval Series | xvi | Englisch | 2014 | Springer | EAN 9789400792579 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]ha…rtmann[at]springer[dot]com | Anbieter: preigu.
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Hardback. Etat : New. 2006 ed. Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the "factual" aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, thes…e aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author's reports from reports of other people's opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers' aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an "NLP"-complete problem.
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Etat : New. A seminal collection of work on computing attitude, affect, and sentimentA balance of conceptual models, computational models, and applicationsCross-disciplinary, catering to a broad audienceAccessible not only to experts, but also t.
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the 'factual' aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to ac…hieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author's reports from reports of other people's opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers' aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an 'NLP'-complete problem.
Langue : anglais
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Hardback. Etat : New. 2006 ed.
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Buch. Etat : Neu. Neuware - Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the 'factual' aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. However, to achieve an adequate understanding of a text, these a…spects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author's reports from reports of other people's opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers' aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an 'NLP'-complete problem.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the 'factual' aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention…. However, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author's reports from reports of other people's opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers' aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an 'NLP'-complete problem. 360 pp. Englisch.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A seminal collection of work on computing attitude, affect, and sentimentA balance of conceptual models, computational models, and applicationsCross-disciplinary, catering to a broad audienceAccessible not only to experts…, but also t.
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Human Language Technology (HLT) and Natural Language Processing (NLP) systems have typically focused on the ¿factual¿ aspect of content analysis. Other aspects, including pragmatics, opinion, and style, have received much less attention. Ho…wever, to achieve an adequate understanding of a text, these aspects cannot be ignored. The chapters in this book address the aspect of subjective opinion, which includes identifying different points of view, identifying different emotive dimensions, and classifying text by opinion. Various conceptual models and computational methods are presented. The models explored in this book include the following: distinguishing attitudes from simple factual assertions; distinguishing between the author¿s reports from reports of other people¿s opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, including indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups about consumer products, political issues, etc. ; brand and reputation management; discovering and predicting consumer and voting trends; analyzing client discourse in therapy and counseling; determining relations between scientific texts by finding reasons for citations; generating more appropriate texts and making agents more believable; and creating writers¿ aids. The studies reported here are carried out on different languages such as English, French, Japanese, and Portuguese. Difficult challenges remain, however. It can be argued that analyzing attitude and affect in text is an ¿NLP¿-complete problem.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 360 pp. Englisch.
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