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Text Relevance and Learning from Text (HC)
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
US$ 41.54
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Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: As New. This book has been in storage since publication and is unread. Hence the description 'as new'. Synopsis: Why do people from similar backgrounds who read the same text construct different meanings? Is there a question behind every reading goal, such that reading is an interactive process of asking and answering of questions? Do people who believe that knowledge is dynamic construct meaning differently than those who believe that knowledge is certain? This volume addresses questions such as these and presents cutting edge research and theory that explores how readers determine text relevance (i.e., the different values they assign to information as they read), how relevance affects understanding, and the implications of these studies for theories of text comprehension. This volume documents in a compelling manner the ongoing international effort to understand how text relevance affects reading and comprehension.
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Text Relevance and Learning from Text (eng)
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Condition: new.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, Incorporated, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Condition: New. pp. 428 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
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Text Relevance and Learning from Text (NA)
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2011. Illustrated. paperback. . . . . .
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 86.31
US$ 16.11 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Text Relevance and Learning from Text (NA)
Language: English
Published by Information Age Publishing 2011-08-01, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
US$ 82.58
US$ 20.83 shipping
Ships from United Kingdom to U.S.A.Quantity: 10 available
Add to basketPaperback. Condition: New.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, Incorporated, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Condition: New. pp. 428.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 83.85
US$ 22.88 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Text Relevance and Learning from Text (NA)
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Condition: New. 2011. Illustrated. paperback. . . . . . Books ship from the US and Ireland.
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Taschenbuch. Condition: Neu. Relevance Instruction in Text Processing | The Effect of Specificity of Relevance Instruction on Reading Time and Learning | Matthew McCrudden | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639138153 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, Incorporated, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
US$ 134.29
US$ 8.74 shipping
Ships from United Kingdom to U.S.A.Quantity: 3 available
Add to basketCondition: New. pp. 428 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
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Text Relevance and Learning from Text (eng)
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Condition: new.
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Machine Learning for Text Document Relevance Ranking
Language: English
Published by LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659233455 ISBN 13: 9783659233456
Taschenbuch. Condition: Neu. Machine Learning for Text Document Relevance Ranking | Arpana Rawal (u. a.) | Taschenbuch | 180 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659233456 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
US$ 144.88
US$ 12.24 shipping
Ships from Ireland to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. 2011. Hardcover. . . . . .
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 142.15
US$ 16.11 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 138.38
US$ 25.26 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. New copy - Usually dispatched within 4 working days.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, Incorporated, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Condition: New. pp. 428.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Condition: New. 2011. Hardcover. . . . . . Books ship from the US and Ireland.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Pub Inc, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
US$ 199.81
US$ 16.81 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketHardcover. Condition: Brand New. 428 pages. 9.50x6.50x1.25 inches. In Stock.
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Machine Learning for Text Document Relevance Ranking
Language: English
Published by LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659233455 ISBN 13: 9783659233456
US$ 188.33
US$ 33.61 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Text Relevance and Learning from Text
Language: English
Published by Emerald Publishing Limited, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
US$ 86.48
US$ 6.75 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Pub Inc, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
US$ 87.04
US$ 16.81 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 428 pages. 9.25x6.25x1.00 inches. In Stock. This item is printed on demand.
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Machine Learning for Text Document Relevance Ranking
Language: English
Published by LAP LAMBERT Academic Publishing Mär 2014, 2014
ISBN 10: 3659233455 ISBN 13: 9783659233456
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The context oriented information retrieval has always been based on some or the other explicit ontologies. The emphasis is laid on on the Implicit Ontologies extracted from input text documents themselves. The research focuses upon design of a system (tool) to rank text documents available in machine-readable format by analyzing them upon softcopies of the syllabus content, through congenial content filtering techniques. The notion of n-gram co-occurrences is used to give the semantic interpretation to the core sentences and their neighboring components. The semantic depths of search key phrases can be learnt by analyzing term-to-term associations from the underlying conceptual dependencies of the extracted content. Two metric measures were chosen for exploring text-semantic depths namely, Topical boundaries and Topical vicinities. The degree of relative relevance was investigated by computing other relevance metric, contextual levels of term-significance from the filtered pages with meaningfully related content. The text-document ranking results were compared for both relevance number and fuzzy-ordering approaches and were found interpretable in finite directions. 180 pp. Englisch.
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Machine Learning for Text Document Relevance Ranking
Language: English
Published by LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659233455 ISBN 13: 9783659233456
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rawal ArpanaDr. A.Rawal is working as Associate Professor in Department of Information Technology at Bhilai Institute of Technology, Durg, Chhattisgarh, India. She has 11 journal and 19 conference publications to her credit. She was .
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Reading is a goal directed activity. Text information that closely matches a reader s goal is more relevant, whereas information that does not match the goal is less relevant. Relevance instructions are prompts that provide criteria for focusing reading goals. Relevance instructions help readers generate goals and specific strategies for reading, allocate resources in a more systematic way, and learn more. This book presents a taxonomy of relevance instructions and summarizes research on this topic. A model of goal-focusing is presented that explains how relevance affects text processing. A study examining the effect of specificity of relevance instructions on reading time and learning is presented.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, Incorporated, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Condition: New. PRINT ON DEMAND pp. 428.
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Text Relevance and Learning from Text
Language: English
Published by Emerald Publishing Limited, 2011
ISBN 10: 1617355305 ISBN 13: 9781617355301
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
US$ 143.45
US$ 12.58 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Text Relevance and Learning from Text
Language: English
Published by Information Age Publishing, 2011
ISBN 10: 1617355291 ISBN 13: 9781617355295
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnWhy do people from similar backgrounds who read the same text construct different meanings? Is there anquestion behind every reading goal, such that reading is an interactive process of asking and answering ofnquestions? Do people.
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Machine Learning for Text Document Relevance Ranking
Language: English
Published by LAP LAMBERT Academic Publishing Mär 2014, 2014
ISBN 10: 3659233455 ISBN 13: 9783659233456
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The context oriented information retrieval has always been based on some or the other explicit ontologies. The emphasis is laid on on the Implicit Ontologies extracted from input text documents themselves. The research focuses upon design of a system (tool) to rank text documents available in machine-readable format by analyzing them upon softcopies of the syllabus content, through congenial content filtering techniques. The notion of n-gram co-occurrences is used to give the semantic interpretation to the core sentences and their neighboring components. The semantic depths of search key phrases can be learnt by analyzing term-to-term associations from the underlying conceptual dependencies of the extracted content. Two metric measures were chosen for exploring text-semantic depths namely, Topical boundaries and Topical vicinities. The degree of relative relevance was investigated by computing other relevance metric, contextual levels of term-significance from the filtered pages with meaningfully related content. The text-document ranking results were compared for both relevance number and fuzzy-ordering approaches and were found interpretable in finite directions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch.
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Machine Learning for Text Document Relevance Ranking
Language: English
Published by LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659233455 ISBN 13: 9783659233456
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The context oriented information retrieval has always been based on some or the other explicit ontologies. The emphasis is laid on on the Implicit Ontologies extracted from input text documents themselves. The research focuses upon design of a system (tool) to rank text documents available in machine-readable format by analyzing them upon softcopies of the syllabus content, through congenial content filtering techniques. The notion of n-gram co-occurrences is used to give the semantic interpretation to the core sentences and their neighboring components. The semantic depths of search key phrases can be learnt by analyzing term-to-term associations from the underlying conceptual dependencies of the extracted content. Two metric measures were chosen for exploring text-semantic depths namely, Topical boundaries and Topical vicinities. The degree of relative relevance was investigated by computing other relevance metric, contextual levels of term-significance from the filtered pages with meaningfully related content. The text-document ranking results were compared for both relevance number and fuzzy-ordering approaches and were found interpretable in finite directions.
