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Managing and Mining Uncertain Data

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
Page : 494 pages
File Size : 33,81 MB
Release : 2010-07-08
Category : Computers
ISBN : 0387096906

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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

Author : Charu C. Aggarwal
Publisher : Springer
Page : 494 pages
File Size : 37,95 MB
Release : 2010-07-08
Category : 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 Graph Data

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
Page : 623 pages
File Size : 36,98 MB
Release : 2010-02-02
Category : Computers
ISBN : 1441960457

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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

Author : Cheqing Jin
Publisher : World Scientific
Page : 165 pages
File Size : 49,13 MB
Release : 2016-05-24
Category : Computers
ISBN : 9813142928

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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.

Mining Graph Data

Author : Diane J. Cook
Publisher : John Wiley & Sons
Page : 501 pages
File Size : 35,26 MB
Release : 2006-12-18
Category : Technology & Engineering
ISBN : 0470073039

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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

Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
Page : 547 pages
File Size : 40,97 MB
Release : 2013-01-15
Category : Computers
ISBN : 1461463092

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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.

Advanced Data Mining and Applications

Author : Jie Tang
Publisher : Springer Science & Business Media
Page : 437 pages
File Size : 40,95 MB
Release : 2011-12-02
Category : Computers
ISBN : 3642258522

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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.

Frequent Pattern Mining

Author : Charu C. Aggarwal
Publisher : Springer
Page : 480 pages
File Size : 31,54 MB
Release : 2014-08-29
Category : Computers
ISBN : 3319078216

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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 : 49,33 MB
Release : 2010-09-27
Category : Computers
ISBN : 3642159508

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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.

Scalable Uncertainty Management

Author : Lluis Godo
Publisher : Springer
Page : 318 pages
File Size : 45,91 MB
Release : 2009-08-29
Category : Computers
ISBN : 3642043887

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This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009. It contains 21 technical papers which were selected out of 30 submitted papers in a rigourous reviewing process. The volume also contains extended abstracts of two invited talks. The volume reflects the growing interest in uncertainty and incosistency and aims at bringing together all those interested in the management of uncertainty and inconsistency at large.