Managing and Mining Uncertain Data

Managing and Mining Uncertain Data
Author: Charu C. Aggarwal
Publsiher: Springer Science & Business Media
Total Pages: 494
Release: 2010-07-08
Genre: Computers
ISBN: 9780387096902

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Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.

Managing and Mining Uncertain Data

Managing and Mining Uncertain Data
Author: Charu C. Aggarwal
Publsiher: Springer
Total Pages: 494
Release: 2010-07-08
Genre: Computers
ISBN: 0387096906

Download Managing and Mining Uncertain Data Book in PDF, Epub and Kindle

Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.

Managing and Mining Graph Data

Managing and Mining Graph Data
Author: Charu C. Aggarwal,Haixun Wang
Publsiher: Springer Science & Business Media
Total Pages: 623
Release: 2010-02-02
Genre: Computers
ISBN: 9781441960450

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Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.

Querying And Mining Uncertain Data Streams

Querying And Mining Uncertain Data Streams
Author: Cheqing Jin,Aoying Zhou
Publsiher: World Scientific
Total Pages: 164
Release: 2016-05-24
Genre: Computers
ISBN: 9789813142923

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Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams cannot be applied to deal with data uncertainty directly due to the exponential growth of possible solution space.This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams. Its contents include some important discoveries dealing with typical topics such as top-k query, ER-Topk query, rarity estimation, set similarity, and clustering.Querying and Mining Uncertain Data Streams is written for professionals, researchers, and graduate students in data mining and its various related fields.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
Author: Thanaruk Theeramunkong,Boonserm Kijsirikul,Nick Cercone,Tu-Bao Ho
Publsiher: Springer Science & Business Media
Total Pages: 1098
Release: 2009-04-20
Genre: Computers
ISBN: 9783642013065

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This book constitutes the refereed proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009, held in Bangkok, Thailand, in April 2009. The 39 revised full papers and 73 revised short papers presented together with 3 keynote talks were carefully reviewed and selected from 338 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.

Mining Graph Data

Mining Graph Data
Author: Diane J. Cook,Lawrence B. Holder
Publsiher: John Wiley & Sons
Total Pages: 501
Release: 2006-12-18
Genre: Technology & Engineering
ISBN: 9780470073032

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This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you’ll be able to represent data as graphs, extract patterns and concepts from the data, and apply the methodologies presented in the text to real datasets. There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their own ideas on graph data, the Web page for the book should be http://www.eecs.wsu.edu/MGD.

Managing and Mining Sensor Data

Managing and Mining Sensor Data
Author: Charu C. Aggarwal
Publsiher: Springer Science & Business Media
Total Pages: 547
Release: 2013-01-15
Genre: Computers
ISBN: 9781461463092

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Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining
Author: Wee Keong Ng
Publsiher: Springer Science & Business Media
Total Pages: 902
Release: 2006-03-31
Genre: Computers
ISBN: 9783540332060

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This book constitutes the refereed proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2006, held in Singapore in April 2006. The 67 revised full papers and 33 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 501 submissions. The papers are organized in topical sections on Classification, Ensemble Learning, Clustering, Support Vector Machines, Text and Document Mining, Web Mining, Bio-Data Mining, and more.