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9783031007842 - Mining Structures of Factual Knowledge from Text: an Effort-light Approach Synthesis Lectures on Data Mining and Knowledge Discovery by Ren, Xiang; Han, Jiawei (13 results)
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Mining Structures of Factual Knowledge from Text: An Effort-Light Approach (Synthesis Lectures on Data Mining and Knowledge Discovery)
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Mining Structures of Factual Knowledge from Text : An Effort-light Approach
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Mining Structures of Factual Knowledge from Text : An Effort-light Approach
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Mining Structures of Factual Knowledge from Text : An Effort-Light Approach
Published by Springer International Publishing, 2018
ISBN 10: 3031007840 ISBN 13: 9783031007842
Language: English
US$ 76.62
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora. Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-valuemining and information extraction. This book introduces this new research frontier and points out some promising research directions.
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Mining Structures of Factual Knowledge from Text
Published by Springer International Publishing, Springer Nature Switzerland Jun 2018, 2018
ISBN 10: 3031007840 ISBN 13: 9783031007842
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware -The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora. Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-valuemining and information extraction. This book introduces this new research frontier and points out some promising research directions.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 200 pp. Englisch.
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Mining Structures of Factual Knowledge from Text
Published by Springer International Publishing Jun 2018, 2018
ISBN 10: 3031007840 ISBN 13: 9783031007842
Language: English
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora. Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-value mining and information extraction. This book introduces this new research frontier and points out some promising research directions. 200 pp. Englisch.
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Mining Structures of Factual Knowledge from Text
Published by Springer International Publishing, 2018
ISBN 10: 3031007840 ISBN 13: 9783031007842
Language: English
US$ 66.57
Convert currencyUS$ 56.77 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Xiang Ren is an Assistant Professor in the Department of Computer Science at USC, affiliated faculty at USC ISI, and a part-time data science advisor at Snap Inc. At USC, Xiang is part of the Machine Learning Center, NLP community, and Center on Knowledge G.
