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Managing and Mining Uncertain Data

Author : Charu C. Aggarwal

Publisher : Springer Science & Business Media

Page : 494 pages

File Size : 17,92 MB

Release : 2010-07-08

Category : Computers

ISBN : 0387096906

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Book Description

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.



Querying And Mining Uncertain Data Streams

Author : Cheqing Jin

Publisher : World Scientific

Page : 165 pages

File Size : 22,86 MB

Release : 2016-05-24

Category : Computers

ISBN : 9813142928

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Book Description

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.



Managing and Mining Graph Data

Author : Charu C. Aggarwal

Publisher : Springer Science & Business Media

Page : 623 pages

File Size : 48,71 MB

Release : 2010-02-02

Category : Computers

ISBN : 1441960457

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Book Description

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.



Advances in Knowledge Discovery and Data Mining

Author : Thanaruk Theeramunkong

Publisher : Springer

Page : 1098 pages

File Size : 44,94 MB

Release : 2009-04-21

Category : Computers

ISBN : 3642013074

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Book Description

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.



Managing and Mining Sensor Data

Author : Charu C. Aggarwal

Publisher : Springer Science & Business Media

Page : 547 pages

File Size : 38,56 MB

Release : 2013-01-15

Category : Computers

ISBN : 1461463092

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Book Description

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.



Managing and Mining Uncertain Data

Author : Charu C. Aggarwal

Publisher : Springer

Page : 494 pages

File Size : 17,56 MB

Release : 2010-07-08

Category : Computers

ISBN : 9780387096902

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Book Description

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.



Advanced Data Mining and Applications

Author : Jie Tang

Publisher : Springer Science & Business Media

Page : 437 pages

File Size : 46,81 MB

Release : 2011-12-02

Category : Computers

ISBN : 3642258522

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Book Description

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed proceedings of the 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, held in Beijing, China, in December 2011. The 35 revised full papers and 29 short papers presented together with 3 keynote speeches were carefully reviewed and selected from 191 submissions. The papers cover a wide range of topics presenting original research findings in data mining, spanning applications, algorithms, software and systems, and applied disciplines.



Mining Graph Data

Author : Diane J. Cook

Publisher : John Wiley & Sons

Page : 501 pages

File Size : 20,27 MB

Release : 2006-12-18

Category : Technology & Engineering

ISBN : 0470073039

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Book Description

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.



Frequent Pattern Mining

Author : Charu C. Aggarwal

Publisher : Springer

Page : 480 pages

File Size : 42,97 MB

Release : 2014-08-29

Category : Computers

ISBN : 3319078216

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Book Description

This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.



Scalable Uncertainty Management

Author : Amol Deshpande

Publisher : Springer Science & Business Media

Page : 399 pages

File Size : 41,86 MB

Release : 2010-09-27

Category : Computers

ISBN : 3642159508

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Book Description

This book constitutes the refereed proceedings of the 4th International Conference on Scalable Uncertainty Management, SUM 2010, held in Toulouse, France, in September 2010. The 26 revised full papers presented together with the abstracts of 2 invited talks and 6 “discussant” contributions were carefully reviewed and selected from 32 submissions. The papers cover all areas of managing substantial and complex kinds of uncertainty and inconsistency in data and knowledge, including applications in decision-support systems, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, text mining, and data mining, and consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.