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Mining User Generated Content
  • Language: en
  • Pages: 446

Mining User Generated Content

  • Type: Book
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  • Published: 2014-01-28
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  • Publisher: CRC Press

Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other networking sites, the social media shared by users and the associated metadata are collectively known as user generated content (UGC). To analyze UGC and glean insight about user behavior, robust techniques are needed to tackle the huge amount of real-time, multimedia,

Proceedings of the Sixth SIAM International Conference on Data Mining
  • Language: en
  • Pages: 662

Proceedings of the Sixth SIAM International Conference on Data Mining

  • Type: Book
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  • Published: 2006-04-01
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  • Publisher: SIAM

The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, based on sound statistical foundations. These techniques in turn require powerful visualization technologies; implementations that must be carefully tuned for performance; software systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them.

Advances in Information Retrieval
  • Language: en
  • Pages: 609

Advances in Information Retrieval

  • Type: Book
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  • Published: 2012-04-05
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  • Publisher: Springer

This book constitutes the proceedings of the 34th European Conference on IR Research, ECIR 2012, held in Barcelona, Spain, in April 2012. The 37 full papers, 28 poster papers and 7 demonstrations presented in this volume were carefully reviewed and selected from 167 submissions. The contributions are organized in sections named: query representation; blogs and online-community search; semi-structured retrieval; evaluation; applications; retrieval models; image and video retrieval; text and content classification, categorisation, clustering; systems efficiency; industry track; and posters.

Vector and Parallel Processing - VECPAR'98
  • Language: en
  • Pages: 721

Vector and Parallel Processing - VECPAR'98

  • Type: Book
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  • Published: 2006-10-11
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  • Publisher: Springer

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Vector and Parallel Processing, VECPAR'98, held in Porto, Portugal, in June 1998. The 41 revised full papers presented were carefully selected during two rounds of reviewing and revision. Also included are six invited papers and introductory chapter surveys. The papers are organized in sections on eigenvalue problems and solutions of linear systems; computational fluid dynamics, structural analysis, and mesh partitioning; computing in education; computer organization, programming and benchmarking; image analysis and synthesis; parallel database servers; and nonlinear problems.

Advances in Information Retrieval
  • Language: en
  • Pages: 630

Advances in Information Retrieval

This two-volume set LNCS 13185 and 13186 constitutes the refereed proceedings of the 44th European Conference on IR Research, ECIR 2022, held in April 2022, due to the COVID-19 pandemic. The 35 full papers presented together with 11 reproducibility papers, 13 CLEF lab descriptions papers, 12 doctoral consortium papers, 5 workshop abstracts, and 4 tutorials abstracts were carefully reviewed and selected from 395 submissions. Chapters “Leveraging Customer Reviews for E-commerce Query Generation” and “End to End Neural Retrieval for Patent Prior Art Search” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Applications of Evolutionary Computing
  • Language: en
  • Pages: 530

Applications of Evolutionary Computing

  • Type: Book
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  • Published: 2003-06-29
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  • Publisher: Springer

This book constitutes the refereed proceedings of five application-oriented workshops held concurrently as EvoWorkshops 2001 in Como, Italy in April 2001. The 52 revised full papers presented were carefully reviewed and selected out of 75 submissions. The papers are organized in topical sections on graph problems, Knapsack problems, ant algorithms, assignment problems, evolutionary algorithms analysis, permutative problems, aeronautics, image analysis and signal processing, evolutionary learning, and evolutionary scheduling and timetabling.

Graph Based Methods for Pattern Mining
  • Language: en
  • Pages: 304

Graph Based Methods for Pattern Mining

  • Type: Book
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  • Published: 2007
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  • Publisher: Unknown

None

Languages, Compilers, and Run-Time Systems for Scalable Computers
  • Language: en
  • Pages: 428

Languages, Compilers, and Run-Time Systems for Scalable Computers

  • Type: Book
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  • Published: 1998-10-07
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  • Publisher: Springer

This book constitutes the strictly refereed post-workshop proceedings of the 4th International Workshop on Languages, Compilers, and Run-Time Systems for Scalable Computing, LCR '98, held in Pittsburgh, PA, USA in May 1998. The 23 revised full papers presented were carefully selected from a total of 47 submissions; also included are nine refereed short papers. All current issues of developing software systems for parallel and distributed computers are covered, in particular irregular applications, automatic parallelization, run-time parallelization, load balancing, message-passing systems, parallelizing compilers, shared memory systems, client server applications, etc.

Proceedings of the Seventh SIAM International Conference on Data Mining
  • Language: en
  • Pages: 674

Proceedings of the Seventh SIAM International Conference on Data Mining

The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question.