rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Journeys to Data Mining
    sub title: Experiences from 15 Renowned Researchers
  name:
    name part: Gaber, Mohamed Medhat.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VIII, 244 p. online resource.
  abstract: Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing. The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions: 1. What are your motives for conducting research in the data mining field? 2. Describe the milestones of your research in this field. 3. What are your notable success stories? 4. How did you learn from your failures? 5. Have you encountered unexpected results? 6. What are the current research issues and challenges in your area? 7. Describe your research tools and techniques. 8. How would you advise a young researcher to make an impact? 9. What do you predict for the next two years in your area? 10. What are your expectations in the long term? In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.
  table of contents: Introduction -- Dean Abbott -- Charu Aggarwal -- Michael Berthold -- John Elder -- Chris Clifton -- David Hand -- Cheryl Howard -- Hillol Kargupta -- Dustin Hux -- Colleen McCue -- Geoff McLachlan -- Gregory Piatetsky-Shapiro -- Shusaku Tsumoto -- Graham Williams -- Mohammed J. Zaki.
  note: edited by Mohamed Medhat Gaber.
  subject:
    topic: Computer science
  subject:
    topic: Mathematical statistics
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Artificial intelligence
  subject:
    topic: Text processing (Computer science)
  subject:
    topic: Computers
  subject:
    topic: Computer Science
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Document Preparation and Text Processing
  subject:
    topic: Probability and Statistics in Computer Science
  subject:
    topic: The Computing Profession
  classification: QA75.5-76.95
  classification: 025.04
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783642280474
  identifier: http://dx.doi.org/10.1007/978-3-642-28047-4
  record info:
    record creation date: 120720
    record change date: 20151103151105.0
    record identifier: 978-3-642-28047-4