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The third SIAM International Conference on Data Mining provided an open forum for the presentation, discussion and development of innovative algorithms, software and theories for data mining applications and data intensive computation. This volume includes 21 research papers.
The two-volume set LNAI 7818 + LNAI 7819 constitutes the refereed proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013, held in Gold Coast, Australia, in April 2013. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 363 submissions. They cover the general fields of data mining and KDD extensively, including pattern mining, classification, graph mining, applications, machine learning, feature selection and dimensionality reduction, multiple information sources mining, social networks, clustering, text mining, text classification, imbalanced data, privacy-preserving data mining, recommendation, multimedia data mining, stream data mining, data preprocessing and representation.
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.
This book constitutes the thoroughly refereed post-proceedings of the 15th International Workshop on Languages and Compilers for Parallel Processing, LCPC 2002, held in College Park, MD, USA in July 2002. The 26 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 32 submissions. All current issues in parallel processing are addressed, in particular memory-constrained computation, compiler optimization, performance studies, high-level languages, programming language consistency models, dynamic parallelization, parallelization of data mining algorithms, parallelizing compilers, garbage collection algorithms, and evaluation of iterative compilation.
This book constitutes the refereed proceedings of the 12th International Conference on Web-Age Information Management, WAIM 2011, held in Wuhan, China in September 2011. The 53 revised full papers presented together with two abstracts and one full paper of the keynote talks were carefully reviewed and selected from a total of 181 submissions. The papers are organized in topical sections on query processing, uncertain data, social media, semantics, data mining, cloud data, multimedia data, user models, data management, graph data, name disambiguation, performance, temporal data, XML, spatial data and event detection.
Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data. This comprehensive book focuses on three primary aspects of data classification: Methods-The book first describes common techniques used for classification, including probabilis...
This book constitutes the refereed proceedings of the 10th International Conference on High-Performance Computing, HiPC 2003, held in Hyderabad, India in December 2003. The 48 revised full papers presented together with 5 keynote abstracts were carefully reviewed and selected from 164 submissions. The papers are organized in topical sections on performance issues and power-aware systems; distributed and network algorithms; routing in wireless, mobile, and cut-through networks; scientific and engineering applications; overlay networks, clusters, and grids; scheduling and software algorithms; network design and performance; grid applications and architecture support; performance analysis; scheduling and migration.
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.
This book constitutes the refereed proceedings of the 10th International Conference on Extending Database Technology, EDBT 2006, held in Munich, Germany, in March 2006. The 60 revised research papers presented together with eight industrial application papers, 20 software demos, and three invited contributions were carefully reviewed and selected from 352 submissions. The papers are organized in topical sections.
This book constitutes the thoroughly refereed post-proceedings of the 14th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2001, held in Lexington, KY, USA, in August 1-3, 2001. The 28 revised full papers presented were carefully selected during two rounds of reviewing and improvement. All current issues in parallel processing are addressed, in particular compiler optimization, HP Java programming, power-aware parallel architectures, high performance applications, power management of mobile computers, data distribution, shared memory systems, load balancing, garbage collection, parallel components, job scheduling, dynamic parallelization, cache optimization, specification, and dataflow analysis.