Issues in the Use of Neural Networks in Information Retrieval, Iatan
Автор: Leif Azzopardi; Gabriella Kazai; Stephen Robertson Название: Advances in Information Retrieval Theory ISBN: 3642044166 ISBN-13(EAN): 9783642044168 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Zbigniew W. Ras; Alicja Wieczorkowska Название: Advances in Music Information Retrieval ISBN: 3642262716 ISBN-13(EAN): 9783642262715 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book collects research performed in music information retrieval domain, and the outcomes, as well as trends in this research. Four sections cover MIR Methods and Platforms, Harmony, Music Similarity, and Content Based Identification and Retrieval.
Автор: Shaoping Ma; Ji-Rong Wen; Yiqun Liu; Zhicheng Dou; Название: Information Retrieval Technology ISBN: 3319480502 ISBN-13(EAN): 9783319480503 Издательство: Springer Рейтинг: Цена: 8106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Lai Название: Information Filtering and Retrieval ISBN: 3319461338 ISBN-13(EAN): 9783319461335 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Brian D. Ripley Название: Pattern Recognition and Neural Networks ISBN: 0521717701 ISBN-13(EAN): 9780521717700 Издательство: Cambridge Academ Рейтинг: Цена: 7762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. Valuable advice is included on both theory and applications, while case studies based on real data sets help readers develop their understanding. All data sets are available from www.stats.ox.ac.uk/~ripley/PRbook/
Автор: Zbigniew W. Ras; Alicja Wieczorkowska Название: Advances in Music Information Retrieval ISBN: 3642116736 ISBN-13(EAN): 9783642116735 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book collects research performed in music information retrieval domain, and the outcomes, as well as trends in this research. Four sections cover MIR Methods and Platforms, Harmony, Music Similarity, and Content Based Identification and Retrieval.
Автор: Bishop, Christopher M. Название: Neural Networks for Pattern Recognition ISBN: 0198538642 ISBN-13(EAN): 9780198538646 Издательство: Oxford Academ Рейтинг: Цена: 13939.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.
Автор: Amihood Amir; Andrew Turpin; Alistair Moffat Название: String Processing and Information Retrieval ISBN: 3540890963 ISBN-13(EAN): 9783540890966 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Mohand Boughanem; Catherine Berrut; Josiane Mothe; Название: Advances in Information Retrieval ISBN: 3642009573 ISBN-13(EAN): 9783642009570 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Shengli Wu Название: Data Fusion in Information Retrieval ISBN: 3642448011 ISBN-13(EAN): 9783642448010 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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