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020 _a9783540362999
_9978-3-540-36299-9
024 7 _a10.1007/11795131
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
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082 0 4 _a006.3
_223
245 1 0 _aRough Sets and Knowledge Technology
_h[electronic resource] :
_bFirst International Conference, RSKT 2006, Chongquing, China, July 24-26, 2006, Proceedings /
_cedited by James F. Peters, Yiju Yao.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aXXII, 810 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v4062
505 0 _aCommemorative Paper -- Keynote Papers -- Plenary Papers -- Rough Computing -- Evolutionary Computing -- Fuzzy Sets -- Granular Computing -- Neural Computing -- Machine Learning and KDD -- Logics and Reasoning -- Multiagent Systems and Web Intelligence -- Pattern Recognition -- System Engineering and Description -- Real-Life Applications Based on Knowledge Technology.
520 _aThis volume contains the papers selected for presentation at the First Int- national Conference on Rough Sets and Knowledge Technology (RSKT 2006) organized in Chongqing, P. R. China, July 24-26, 2003. There were 503 s- missions for RSKT 2006 except for 1 commemorative paper, 4 keynote papers and 10 plenary papers. Except for the 15 commemorative and invited papers, 101 papers were accepted by RSKT 2006 and are included in this volume. The acceptance rate was only 20%. These papers were divided into 43 regular oral presentation papers (each allotted 8 pages), and 58 short oral presentation - pers (each allotted 6 pages) on the basis of reviewer evaluation. Each paper was reviewed by two to four referees. Since the introduction of rough sets in 1981 by Zdzis law Pawlak, many great advances in both the theory and applications have been introduced. Rough set theory is closely related to knowledge technology in a variety of forms such as knowledge discovery, approximate reasoning, intelligent and multiagent systems design, and knowledge intensive computations that signal the emergence of a knowledge technology age. The essence of growth in cutting-edge, state-of-t- art and promising knowledge technologies is closely related to learning, pattern recognition,machine intelligence and automation of acquisition, transformation, communication, exploration and exploitation of knowledge. A principal thrust of such technologies is the utilization of methodologies that facilitate knowledge processing.
650 0 _aArtificial intelligence.
650 0 _aInformation storage and retrieval systems.
650 0 _aDatabase management.
650 0 _aMachine theory.
650 0 _aComputer science.
650 0 _aPattern recognition systems.
650 1 4 _aArtificial Intelligence.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aDatabase Management.
650 2 4 _aFormal Languages and Automata Theory.
650 2 4 _aTheory of Computation.
650 2 4 _aAutomated Pattern Recognition.
700 1 _aPeters, James F.
_eeditor.
_0(orcid)
_10000-0002-1026-4638
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aYao, Yiju.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540362975
776 0 8 _iPrinted edition:
_z9783540826606
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v4062
856 4 0 _uhttps://doi.org/10.1007/11795131
912 _aZDB-2-SCS
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