Next-Generation Information Retrieval and Knowledge Resources Management, Joan Lu

Автор: Xiang Ren, Jiawei Han
Название: Mining Structures of Factual Knowledge from Text: An Effort-Light Approach
ISBN: 1681733943 ISBN-13(EAN): 9781681733944
Издательство: Mare Nostrum (Eurospan)
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Цена: 102570.00 T
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Описание: 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.

Автор: Xiang Ren, Jiawei Han
Название: Mining Structures of Factual Knowledge from Text: An Effort-Light Approach
ISBN: 1681733927 ISBN-13(EAN): 9781681733920
Издательство: Mare Nostrum (Eurospan)
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Цена: 82230.00 T
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Описание: 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.

Автор: Yishai Feldman; Donald Kraft; Tsvi Kuflik
Название: Next Generation Information Technologies and Systems
ISBN: 3642049400 ISBN-13(EAN): 9783642049408
Издательство: Springer
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Цена: 65210.00 T
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Автор: Lai
Название: Information Filtering and Retrieval
ISBN: 3319461338 ISBN-13(EAN): 9783319461335
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book focuses on new research challenges in intelligent information filtering and retrieval. It collects invited chapters and extended research contributions from DART 2014 (the 8th International Workshop on Information Filtering and Retrieval), held in Pisa (Italy), on December 10, 2014, and co-hosted with the XIII AI*IA Symposium on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The chapters of this book present a comprehensive review of related works and the current state of the art. The contributions from both practitioners and researchers have been carefully reviewed by experts in the area, who also gave useful suggestions to improve the quality of the book.

Автор: Shaoping Ma; Ji-Rong Wen; Yiqun Liu; Zhicheng Dou;
Название: Information Retrieval Technology
ISBN: 3319480502 ISBN-13(EAN): 9783319480503
Издательство: Springer
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Цена: 54040.00 T
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Описание: This book constitutes the refereed proceedings of the 12th Information Retrieval Societies Conference, AIRS 2016, held in Beijing, China, in November/December 2016. The 21 full papers presented together with 11 short papers were carefully reviewed and selected from 57 submissions.

Автор: Lu
Название: Information Retrieval Methods For Multidisciplinary Applications
ISBN: 1466638982 ISBN-13(EAN): 9781466638983
Издательство: Mare Nostrum (Eurospan)
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Цена: 170010.00 T
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Описание: The internet provides a vast amount of data which can be utilised to explore different approaches to solving industry problems. Efficient methods for the retrieval of this information are essential for streamlined business processes. <em>Information Retrieval Methods for Multidisciplinary Applications</em> provides innovative research on information gathering, web data mining, and automation systems. Addressing multidisciplinary applications and focusing on theories and methods with an enterprise-wide perspective, this book is essential for information engineers, scientists, and related professionals.

Автор: Hagit Shatkay; Christian Blaschke
Название: Linking, Literature, Information, and Knowledge for Biologie
ISBN: 3642131301 ISBN-13(EAN): 9783642131301
Издательство: Springer
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Цена: 65210.00 T
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Описание: Contains selected papers from the workshop of the BioLINK Special Interest Group (SIG) on Linking Literature, Information and Knowledge for Biology. The workshop was held June 28- 29, 2009 at the ISMB/ECCB 2009 conference in Stockholm.

Автор: Shengli Wu
Название: Data Fusion in Information Retrieval
ISBN: 3642448011 ISBN-13(EAN): 9783642448010
Издательство: Springer
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Цена: 121890.00 T
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Описание: This book offers a theoretical and empirical approach to data fusion, used in information retrieval in complex, diverse settings such as web and social networks, legal, enterprise and others. Discusses, analyzes and ealuates typical data fusion algorithms.

Автор: Mohand Boughanem; Catherine Berrut; Josiane Mothe;
Название: Advances in Information Retrieval
ISBN: 3642009573 ISBN-13(EAN): 9783642009570
Издательство: Springer
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Цена: 121110.00 T
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Описание: Constitutes the refereed proceedings of the 30th annual European Conference on Information Retrieval Research, ECIR 2009, held in Toulouse, France in April 2009. This book presents 42 revised full papers and 18 revised short papers with the abstracts of 3 invited lectures and 25 poster papers that were reviewed and selected from 188 submissions.

Автор: Amihood Amir; Andrew Turpin; Alistair Moffat
Название: String Processing and Information Retrieval
ISBN: 3540890963 ISBN-13(EAN): 9783540890966
Издательство: Springer
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Цена: 65210.00 T
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Описание: Constitutes the refereed proceedings of the 15th International Symposium on String Processing and Information Retrieval, SPIRE 2008, held in Melbourne, Australia, in November 2008. This book presents the papers that are organized in topical sections on compression and performance, information retrieval scoring and ranking, and self-indexing.

Автор: Dawei Song; Chin-Yew Lin; Akiko Aizawa; Kazuko Kur
Название: Information Retrieval Technology
ISBN: 3642047688 ISBN-13(EAN): 9783642047688
Издательство: Springer
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Цена: 83850.00 T
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Описание: This book constitutes the refereed proceedings of the 5th Asia Information Retrieval Symposium, AIRS 2009, held in Sapporo, Japan, in October 2009. The 18 revised full papers and 20 revised poster papers presented were carefully reviewed and selected from 82 submissions.

Автор: Leif Azzopardi; Gabriella Kazai; Stephen Robertson
Название: Advances in Information Retrieval Theory
ISBN: 3642044166 ISBN-13(EAN): 9783642044168
Издательство: Springer
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Цена: 83850.00 T
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Описание: The papers are categorized into four main themes: novel IR models, evaluation, efficiency, and new perspectives in IR. Twenty-one papers fall into the general theme of novel IR models, ranging from various retrieval models, query and term selection models, Web IR models, developments in novelty and diversity, to the modeling of user aspects.