Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200242135 ISBN 13: 9786200242136
Language: English
Seller: moluna, Greven, Germany
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Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200242135 ISBN 13: 9786200242136
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketPaperback. Condition: Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock.
Published by LAP LAMBERT Academic Publishing Jul 2019, 2019
ISBN 10: 6200242135 ISBN 13: 9786200242136
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Add to basketTaschenbuch. Condition: Neu. Neuware -This book introduces Relational Markov Networks (RMN¿s) for Collective Information Extraction. Also, an attempt has been made to improve the performance of Relational Markov Network using Approximate Inference Procedure such as Gibbs Sampling for Collective Information Extraction. Gibbs Sampling has been used for making the performance of LT-RMN¿s better than CRF¿s for Collective Information Extraction.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch.
Published by LAP LAMBERT Academic Publishing Jul 2019, 2019
ISBN 10: 6200242135 ISBN 13: 9786200242136
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces Relational Markov Networks (RMN's) for Collective Information Extraction. Also, an attempt has been made to improve the performance of Relational Markov Network using Approximate Inference Procedure such as Gibbs Sampling for Collective Information Extraction. Gibbs Sampling has been used for making the performance of LT-RMN's better than CRF's for Collective Information Extraction. 76 pp. Englisch.
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200242135 ISBN 13: 9786200242136
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduces Relational Markov Networks (RMN's) for Collective Information Extraction. Also, an attempt has been made to improve the performance of Relational Markov Network using Approximate Inference Procedure such as Gibbs Sampling for Collective Information Extraction. Gibbs Sampling has been used for making the performance of LT-RMN's better than CRF's for Collective Information Extraction.