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Understanding Editorial Text: A Computer Model of Argument Comprehension: 107 (The Springer International Series in Engineering and Computer Science) - Softcover
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by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual representations, linked by causal relationships and organized/indexed for subsequent retrieval. Once these conceptual representations have been created, comprehension can be tested by means of such tasks as paraphrasing, question answering, and summarization. Higher-level cognitive tasks are also modeled within the NLP paradigm and include: translation, acquisition of word meanings and concepts through reading, analysis of goals and plans in multi-agent environments (e. g. , coalition and counterplanning behavior by narrative characters), invention of novel stories, recognition of abstract themes (such as irony and hypocrisy), extraction of the moral or point of a story, and justification/refutation of beliefs through argumentation. The robustness of conceptually-based text comprehension systems is directly related to the nature and scope of the knowledge constructs applied during conceptual analysis of the text. Until recently, conceptually-based natural language systems were developed for, and applied to, the task of narrative comprehension (Dyer, 1983a; Schank and Abelson, 1977; Wilensky, 1983). These systems worked by recognizing the goals and plans of narrative characters, and. using this knowledge to build a conceptual representation of the narrative, xx UNDERSTANDING EDITORIAL TEXT including actions and intentions which must be inferred to complete the representation. A large portion of text appearing in newspapers and magazines, however, is editorial in nature.
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by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual representations, linked by causal relationships and organized/indexed for subsequent retrieval. Once these conceptual representations have been created, comprehension can be tested by means of such tasks as paraphrasing, question answering, and summarization. Higher-level cognitive tasks are also modeled within the NLP paradigm and include: translation, acquisition of word meanings and concepts through reading, analysis of goals and plans in multi-agent environments (e. g. , coalition and counterplanning behavior by narrative characters), invention of novel stories, recognition of abstract themes (such as irony and hypocrisy), extraction of the moral or point of a story, and justification/refutation of beliefs through argumentation. The robustness of conceptually-based text comprehension systems is directly related to the nature and scope of the knowledge constructs applied during conceptual analysis of the text. Until recently, conceptually-based natural language systems were developed for, and applied to, the task of narrative comprehension (Dyer, 1983a; Schank and Abelson, 1977; Wilensky, 1983). These systems worked by recognizing the goals and plans of narrative characters, and. using this knowledge to build a conceptual representation of the narrative, xx UNDERSTANDING EDITORIAL TEXT including actions and intentions which must be inferred to complete the representation. A large portion of text appearing in newspapers and magazines, however, is editorial in nature.
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Understanding Editorial Text: A Computer Model of Argument Comprehension
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual represent. Bestandsnummer des Verkäufers 4191390
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Understanding Editorial Text: A Computer Model of Argument Comprehension
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Springer New York, Springer US Sep 2011, 2011
ISBN 10: 1461288363
ISBN 13: 9781461288367
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual representations, linked by causal relationships and organized/indexed for subsequent retrieval. Once these conceptual representations have been created, comprehension can be tested by means of such tasks as paraphrasing, question answering, and summarization. Higher-level cognitive tasks are also modeled within the NLP paradigm and include: translation, acquisition of word meanings and concepts through reading, analysis of goals and plans in multi-agent environments (e. g. , coalition and counterplanning behavior by narrative characters), invention of novel stories, recognition of abstract themes (such as irony and hypocrisy), extraction of the moral or point of a story, and justification/refutation of beliefs through argumentation. The robustness of conceptually-based text comprehension systems is directly related to the nature and scope of the knowledge constructs applied during conceptual analysis of the text. Until recently, conceptually-based natural language systems were developed for, and applied to, the task of narrative comprehension (Dyer, 1983a; Schank and Abelson, 1977; Wilensky, 1983). These systems worked by recognizing the goals and plans of narrative characters, and. using this knowledge to build a conceptual representation of the narrative, xx UNDERSTANDING EDITORIAL TEXT including actions and intentions which must be inferred to complete the representation. A large portion of text appearing in newspapers and magazines, however, is editorial in nature.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch. Bestandsnummer des Verkäufers 9781461288367
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Understanding Editorial Text: A Computer Model of Argument Comprehension
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual representations, linked by causal relationships and organized/indexed for subsequent retrieval. Once these conceptual representations have been created, comprehension can be tested by means of such tasks as paraphrasing, question answering, and summarization. Higher-level cognitive tasks are also modeled within the NLP paradigm and include: translation, acquisition of word meanings and concepts through reading, analysis of goals and plans in multi-agent environments (e. g. , coalition and counterplanning behavior by narrative characters), invention of novel stories, recognition of abstract themes (such as irony and hypocrisy), extraction of the moral or point of a story, and justification/refutation of beliefs through argumentation. The robustness of conceptually-based text comprehension systems is directly related to the nature and scope of the knowledge constructs applied during conceptual analysis of the text. Until recently, conceptually-based natural language systems were developed for, and applied to, the task of narrative comprehension (Dyer, 1983a; Schank and Abelson, 1977; Wilensky, 1983). These systems worked by recognizing the goals and plans of narrative characters, and. using this knowledge to build a conceptual representation of the narrative, xx UNDERSTANDING EDITORIAL TEXT including actions and intentions which must be inferred to complete the representation. A large portion of text appearing in newspapers and magazines, however, is editorial in nature. 328 pp. Englisch. Bestandsnummer des Verkäufers 9781461288367
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Understanding Editorial Text: A Computer Model of Argument Comprehension
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - by Michael G. Dyer Natural language processing (NLP) is an area of research within Artificial Intelligence (AI) concerned with the comprehension and generation of natural language text. Comprehension involves the dynamic construction of conceptual representations, linked by causal relationships and organized/indexed for subsequent retrieval. Once these conceptual representations have been created, comprehension can be tested by means of such tasks as paraphrasing, question answering, and summarization. Higher-level cognitive tasks are also modeled within the NLP paradigm and include: translation, acquisition of word meanings and concepts through reading, analysis of goals and plans in multi-agent environments (e. g. , coalition and counterplanning behavior by narrative characters), invention of novel stories, recognition of abstract themes (such as irony and hypocrisy), extraction of the moral or point of a story, and justification/refutation of beliefs through argumentation. The robustness of conceptually-based text comprehension systems is directly related to the nature and scope of the knowledge constructs applied during conceptual analysis of the text. Until recently, conceptually-based natural language systems were developed for, and applied to, the task of narrative comprehension (Dyer, 1983a; Schank and Abelson, 1977; Wilensky, 1983). These systems worked by recognizing the goals and plans of narrative characters, and. using this knowledge to build a conceptual representation of the narrative, xx UNDERSTANDING EDITORIAL TEXT including actions and intentions which must be inferred to complete the representation. A large portion of text appearing in newspapers and magazines, however, is editorial in nature. Bestandsnummer des Verkäufers 9781461288367
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Understanding Editorial Text: A Computer Model of Argument Comprehension (The Springer International Series in Engineering and Computer Science)
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Understanding Editorial Text
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Understanding Editorial Text: A Computer Model of Argument Comprehension (The Springer International Series in Engineering and Computer Science)
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Understanding Editorial Text: A Computer Model of Argument Comprehension (The Springer International Series in Engineering and Computer Science, 107)
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