000 03911nam a22005055i 4500
001 978-3-642-28047-4
003 DE-He213
005 20140220083310.0
007 cr nn 008mamaa
008 120720s2012 gw | s |||| 0|eng d
020 _a9783642280474
_9978-3-642-28047-4
024 7 _a10.1007/978-3-642-28047-4
_2doi
050 4 _aQA75.5-76.95
072 7 _aUNH
_2bicssc
072 7 _aUND
_2bicssc
072 7 _aCOM030000
_2bisacsh
082 0 4 _a025.04
_223
100 1 _aGaber, Mohamed Medhat.
_eeditor.
245 1 0 _aJourneys to Data Mining
_h[electronic resource] :
_bExperiences from 15 Renowned Researchers /
_cedited by Mohamed Medhat Gaber.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2012.
300 _aVIII, 241 p. 33 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction -- 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.
520 _aData 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.
650 0 _aComputer science.
650 0 _aInformation storage and retrieval systems.
650 0 _aArtificial intelligence.
650 0 _aText processing (Computer science.
650 0 _aComputer industry.
650 1 4 _aComputer Science.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aDocument Preparation and Text Processing.
650 2 4 _aProbability and Statistics in Computer Science.
650 2 4 _aThe Computing Profession.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642280467
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-28047-4
912 _aZDB-2-SCS
999 _c102710
_d102710