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Titlebook: Rough Sets and Knowledge Technology; First International Guo-Ying Wang,James F. Peters,Yiyu Yao Conference proceedings 2006 Springer-Verla

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書目名稱Rough Sets and Knowledge Technology
副標(biāo)題First International
編輯Guo-Ying Wang,James F. Peters,Yiyu Yao
視頻videohttp://file.papertrans.cn/832/831918/831918.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Rough Sets and Knowledge Technology; First International  Guo-Ying Wang,James F. Peters,Yiyu Yao Conference proceedings 2006 Springer-Verla
描述This 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 kn
出版日期Conference proceedings 2006
關(guān)鍵詞Web Intelligence; cognition; evolution; evolutionary computation; fuzzy; intelligence; knowledge; learning;
版次1
doihttps://doi.org/10.1007/11795131
isbn_softcover978-3-540-36297-5
isbn_ebook978-3-540-36299-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2006
The information of publication is updating

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Rough Sets and Knowledge Technology978-3-540-36299-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Partition Dependencies in Hierarchies of Probabilistic Decision TablesThe article investigates probabilistic dependencies in hierarchies of probabilistic decision tables learned from data. They are expressed by the probabilistic generalization of the Pawlak’s measure of the dependency between attributes and the certainty gain measure.
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as beginners or as experts in the field and who want to getThe years 2006 and 2007 mark a dramatic change of peoples view regarding c- mate change and energy consumption. The new IPCC report makes clear that - mankind plays a dominant role on climate change due to CO emissions from en- 2 ergy consu
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