LEADER 05431nam 22008055 450 001 996465400003316 005 20220812234343.0 024 7 $a10.1007/11548706 035 $a(CKB)1000000000213217 035 $a(SSID)ssj0000319887 035 $a(PQKBManifestationID)11235122 035 $a(PQKBTitleCode)TC0000319887 035 $a(PQKBWorkID)10338790 035 $a(PQKB)10255707 035 $a(DE-He213)978-3-540-31824-8 035 $a(MiAaPQ)EBC3067879 035 $a(PPN)123097126 035 $a(EXLCZ)991000000000213217 100 $a20100725d2005 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aRough Sets, Fuzzy Sets, Data Mining, and Granular Computing$b[electronic resource] $e10th International Conference, RSFDGrC 2005, Regina, Canada, August 31 - September 2, 2005, Proceedings, Part II /$fedited by Dominik Slezak, JingTao Yao, James F. Peters, Wojciech Ziarko, Xiaohua Hu 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (XXIV, 748 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v3642 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-31824-0 311 $a3-540-28660-8 320 $aIncludes bibliographical references and index. 327 $aInvited Papers -- Rough Set Software -- Data Mining -- Hybrid and Hierarchical Methods -- Information Retrieval -- Image Recognition and Processing -- Multimedia Applications -- Medical Applications -- Bioinformatic Applications -- Web Content Analysis -- Business Applications -- Security Applications -- Industrial Applications -- Embedded Systems and Networking -- Intelligent and Sapient Systems. 330 $aThis volume contains the papers selected for presentation at the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st?September 3rd, 2005. This conference followed in the footsteps of international events devoted to the subject of rough sets, held so far in Canada, China, Japan, Poland, Sweden, and the USA. RSFDGrC achieved the status of biennial international conference, starting from 2003 in Chongqing, China. The theory of rough sets, proposed by Zdzis law Pawlak in 1982, is a model of approximate reasoning. The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to significant results in many areas such as finance, industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granular computing, and knowledge discovery and data mining, both at the level of theoretical foundations and real-life applications. In the case of this event, additional effort was made to establish a linkage towards a broader range of applications. We achieved it by including in the conference program the workshops on bioinformatics, security engineering, and embedded systems, as well as tutorials and sessions related to other application areas. 410 0$aLecture Notes in Artificial Intelligence ;$v3642 606 $aArtificial intelligence 606 $aInformation storage and retrieval 606 $aDatabase management 606 $aMathematical logic 606 $aComputers 606 $aPattern recognition 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 615 0$aArtificial intelligence. 615 0$aInformation storage and retrieval. 615 0$aDatabase management. 615 0$aMathematical logic. 615 0$aComputers. 615 0$aPattern recognition. 615 14$aArtificial Intelligence. 615 24$aInformation Storage and Retrieval. 615 24$aDatabase Management. 615 24$aMathematical Logic and Formal Languages. 615 24$aComputation by Abstract Devices. 615 24$aPattern Recognition. 676 $a006.3 702 $aSlezak$b Dominik$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aYao$b JingTao$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPeters$b James F$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZiarko$b Wojciech$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHu$b Xiaohua$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996465400003316 996 $aRough Sets, Fuzzy Sets, Data Mining and Granular Computing$9772384 997 $aUNISA LEADER 00902nam a2200253 i 4500 001 991001247839707536 005 20020507113407.0 008 970308s1969 us ||| | eng 035 $ab10194137-39ule_inst 035 $aLE00644610$9ExL 040 $aDip.to Fisica$bita 084 $a53.7.8 100 1 $aGreen, M.$0348041 245 10$aSolid state surface science /$cedited by M. 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