Rough sets and current trends in computing. 3rd international conference, RSCTC 2002, Malvern, PA, USA, October 14--16, 2002. Proceedings
The articles of this volume will be reviewed individually. The preceding conference (2nd, 2000) has been reviewed (see Zbl 0978.00041). Indexed articles: \textit{Pawlak, Zdzisław}, In pursuit of patterns in data reasoning from data --- the rough set way, 1-9 [Zbl 1013.68585] \textit{Zadeh, Lotfi A.}, Toward a theory of hierarchical definability (THD). Causality is undefinable, 10-12 [Zbl 1013.68605] \textit{Komorowski, Jan}, Modelling biological phenomena with rough sets, 13 [Zbl 1013.68590] \textit{Lin, Tsau Young}, Database mining on derived attributes. Granular and rough computing approach, 14-32 [Zbl 1013.68575] \textit{Russell, David W.}, A proposed evolutionary, self-organizing automaton for the control of dynamic systems, 33-43 [Zbl 1013.93500] \textit{Słowiński, Roman; Greco, Salvatore; Matarazzo, Benedetto}, Rough set analysis of preference-ordered data, 44-59 [Zbl 1013.68599] \textit{Türksen, I. B.}, Fuzzy sets, multi-valued mappings, and rough sets, 60 [Zbl 1013.68579] \textit{Beynon, Malcolm J.}, Investigating the choice of \(l\) and \(u\) values in the extended variable precision rough sets model, 61-68 [Zbl 1013.68615] \textit{Cattaneo, Gianpiero; Ciucci, Davide}, A quantitative analysis of preclusivity vs. similarity based rough approximations, 69-76 [Zbl 1013.68564] \textit{Cattaneo, Gianpiero; Ciucci, Davide}, Heyting Wajsberg algebras as an abstract environment linking fuzzy and rough sets, 77-84 [Zbl 1013.03073] \textit{Greco, Salvatore; Inuiguchi, Masahiro; Słowiński, Roman}, Dominance-based rough set approach using possibility and necessity measures, 85-92 [Zbl 1013.91502] \textit{Greco, Salvatore; Pawlak, Zdzisław; Słowiński, Roman}, Generalized decision algorithms, rough inference rules, and flow graphs, 93-104 [Zbl 1013.91503] \textit{Inuiguchi, Masahiro; Tanino, Tetsuzo}, Generalized rough sets and rule extraction, 105-112 [Zbl 1013.68581] \textit{Janicki, Ryszard}, Towards a mereological system for direct products and relations, 113-122 [Zbl 1013.03076] \textit{Järvinen, Jouni}, On the structure of rough approximations, 123-130 [Zbl 1013.68592] \textit{Katarzyniak, Radoslaw; Nguyen, Ngoc Thanh}, Modification of weights of conflict profile's elements and dependencies of attributes in consensus model, 131-138 [Zbl 1013.68243] \textit{Liu, Qing; Jiang, S. L.}, Reasoning about information granules based on rough logic, 139-143 [Zbl 1013.68596] \textit{Midelfart, Herman; Komorowski, Jan}, A rough set framework for learning in a directed acyclic graph, 144-155 [Zbl 1013.68565] \textit{Moshkov, Mikhail}, On compressible information systems, 156-160 [Zbl 1013.68591] \textit{Nakata, Michinori; Murai, Tetsuya}, Functional dependencies in relational expressions based on or-sets, 161-166 [Zbl 1013.68500] \textit{Polkowski, Lech}, On asymptotic properties of rough-set-theoretic approximations. Fractal dimension, exact sets, and rough inclusion in potentially infinite information systems, 167-174 [Zbl 1013.68239] \textit{Pomykała, J. A.}, About tolerance and similarity relations in information systems, 175-182 [Zbl 1013.68566] \textit{Ramsey, Frederick V.; Alpigini, James J.}, Rough sets, guarded command language, and decision rules, 183-188 [Zbl 1013.68600] \textit{Ras, Zbigniew W.; Dardzińska, Agnieszka}, Collaborative query processing in DKS controlled by reducts, 189-196 [Zbl 1013.68573] \textit{Rzasa, Wojciech; Suraj, Zbigniew}, A new method for determining of extensions and restrictions of information systems, 197-204 [Zbl 1013.68612] \textit{Vitória, Aida; Małuszyński, Jan}, A logic programming framework for rough sets, 205-212 [Zbl 1013.68562] \textit{Wang, G. Y.}, Attribute core of decision table, 213-217 [Zbl 1013.68571] \textit{Borkowski, Maciej}, Signal analysis using rough integrals, 218-225 [Zbl 1013.94509] \textit{Chiang, Yi-Ting; Chiang, Yu-Cheng; Hsu, Tsan-sheng; Liau, Churn-Jung; Wang, Da-Wei}, How much privacy? --- A system to safe guard personal privacy while releasing databases, 226-233 [Zbl 1013.68888] \textit{do Prado, Hércules Antonio; Engel, Paulo Martins; Filho, Homero Chaib}, Rough clustering: An alternative to find meaningful clusters by using the reducts from a dataset, 234-238 [Zbl 1013.68613] \textit{Dubois, Vincent; Quafafou, Mohamed}, Concept learning with approximation: Rough version spaces, 239-246 [Zbl 1013.68574] \textit{Giove, Silvio; Greco, Salvatore; Matarazzo, Benedetto; Słowiński, Roman}, Variable consistency monotonic decision trees, 247-254 [Zbl 1013.68608] \textit{Greco, Salvatore; Matarazzo, Benedetto; Slowinski, Roman; Stefanowski, Jerzy}, Importance and interaction of conditions in decision rules, 255-262 [Zbl 1013.68584] \textit{Lingras, Pawan; Yao, Y. Y.}, Time complexity of rough clustering: GAs versus K-means, 263-270 [Zbl 1013.68604] \textit{Stefanowski, Jerzy; Tsoukiàs, Alexis}, Induction of decision rules and classification in the valued tolerance approach, 271-278 [Zbl 1013.68587] \textit{Valdés, Julio J.; Mateescu, Gabriel}, Time series model mining with similarity-based neuro-fuzzy networks and genetic algorithms: A parallel implementation, 279-288 [Zbl 1013.68609] \textit{Alpigini, James J.}, Closeness of performance map information granules: A rough set approach, 289-295 [Zbl 1013.68572] \textit{Lin, Tsau Young}, Granular computing on binary relations, 296-299 [Zbl 1013.68582] \textit{Peters, James F.; Skowron, Andrzej; Suraj, Zbigniew; Borkowski, Maciej; Rzasa, Wojciech}, Measures of inclusion and closeness of information granules: A rough set approach, 300-307 [Zbl 1013.68610] \textit{Peters, James F.; Szczuka, Marcin S.}, Rough neurocomputing: A survey of basic models of neurocomputation, 308-315 [Zbl 1013.68521] \textit{Skowron, Andrzej; Stepaniuk, Jarosław; Peters, James F.}, Rough neurocomputing based on hierarchical classifiers, 316-323 [Zbl 1013.68520] \textit{Yager, Ronald R.}, Using granular objects in multi-source data fusion, 324-330 [Zbl 1013.68607] \textit{Yao, J. T.; Yao, Y. Y.}, Induction of classification rules by granular computing, 331-338 [Zbl 1013.68514] \textit{Butz, C. J.; Sanscartier, M. J.}, Acquisition methods for contextual weak independence, 339-343 [Zbl 1013.68568] \textit{Butz, C. J.; Sanscartier, M. J.}, A method for detecting context-specific independence in conditional probability tables, 344-348 [Zbl 1013.68614] \textit{Butz, C. J.; Sanscartier, M. J.}, Properties of weak conditional independence, 349-356 [Zbl 1013.68594] \textit{Intan, Rolly; Mukaidono, Masao}, A proposal of probability of rough event based on probability of fuzzy event, 357-364 [Zbl 1013.68563] \textit{Slezak, Dominik; Wróblewski, Jakub}, Approximate Bayesian network classifiers, 365-372 [Zbl 1013.68569] \textit{Tsumoto, Shusaku}, Accuracy and coverage in rough set rule induction, 373-380 [Zbl 1013.68567] \textit{Tsumoto, Shusaku}, Statistical test for rough set approximation based on Fisher's exact test, 381-388 [Zbl 1013.68603] \textit{Wong, S. K. M.; Wu, D.; Butz, C. J.}, Triangulation of Bayesian networks: A relational database perspective, 389-396 [Zbl 1013.68237] \textit{Bazan, Jan G.; Szczuka, Marcin S.; Wróblewski, Jakub}, A new version of rough set exploration system, 397-404 [Zbl 1013.68643] \textit{Góra, Grzegorz; Wojna, Arkadiusz}, Local attribute value grouping for lazy rule induction, 405-412 [Zbl 1013.68589] \textit{Latkowski, Rafał}, Incomplete data decomposition for classification, 413-420 [Zbl 1013.68586] \textit{Martinez, Juan F.; Wasilewska, Anita; Hadjimichael, Michael; Fernandez, Covadonga; Menasalvas, Ernestina}, Extension of relational management systems with data mining capabilities, 421-424 [Zbl 1013.68578] \textit{Mikołajczyk, Michał}, Reducing number of decision rules by joining, 425-432 [Zbl 1013.68597] \textit{Nguyen, Hung Son}, Scalable classification method based on rough sets, 433-440 [Zbl 1013.68601] \textit{Peña, José M.; Crespo, F. Javier; Menasalvas, Ernestina; Robles, Victor}, Parallel data mining experimentation using flexible configurations, 441-448 [Zbl 1013.68815] \textit{Pérez, María S.; Pons, Ramón A.; García, Félix; Carretero, Jesús; Córdoba, María L.}, An optimization of Apriori algorithm through the usage of parallel I/O and hints, 449-452 [Zbl 1013.68669] \textit{Skowron, Andrzej; Synak, Piotr}, Patterns in information maps, 453-460 [Zbl 1013.68593] \textit{Zhao, Min; Wang, Jue}, Discernibility matrix approach to exception analysis, 461-466 [Zbl 1013.68576] \textit{Zhong, Ning; Dong, Ju-Zhen; Yao, Y. Y.; Ohsuga, Setsuo}, Gastric cancer data mining with ordered information, 467-478 [Zbl 1013.68580] \textit{Hochsztain, Esther; Millán, Socorro; Menasalvas, Ernestina}, A granular approach for analyzing the degree of affability of a web site, 479-486 [Zbl 1013.68631] \textit{Hu, Xiaohua}, Comparison of classification methods for customer attrition analysis, 487-492 [Zbl 1013.68696] \textit{Li, Yuefeng; Yao, Y. Y.}, User profile model: A view from artificial intelligence, 493-496 [Zbl 1013.68868] \textit{Marban, Oscar; Segovia, Javier; Cuadrado, Juan J.; Montes, Cesar}, Mining the client's life cycle behaviour in the web, 497-505 [Zbl 1013.68787] \textit{Yao, Y. Y.; Hamilton, H. J.; Wang, Xuewei}, PagePrompter: An intelligent web agent created using data mining techniques, 506-513 [Zbl 1013.68814] \textit{Ziarko, Wojciech; Fei, Xue}, VPRSM approach to WEB searching, 514-521 [Zbl 1013.68501] \textit{Bazan, Jan; Osmólski, Antoni; Skowron, Andrzej; Slezak, Dominik; Szczuka, Marcin; Wróblewski, Jakub}, Rough set approach to the survival analysis, 522-529 [Zbl 1013.68833] \textit{Beynon, Malcolm J.}, The identification of low-paying workplaces: An analysis using the variable precision rough sets model, 530-537 [Zbl 1013.68611] \textit{Grzymała-Busse, Jerzy W.; Hippe, Zdzisław S.}, A search for the best data mining method to predict melanoma, 538-545 [Zbl 1013.68645] \textit{Hippe, Monika P.}, Towards the classification of musical works: A rough set approach, 546-553 [Zbl 1013.68606] \textit{Hirano, Shoji; Tsumoto, Shusaku}, Segmentation of medical images based on approximations in rough set theory, 554-563 [Zbl 1013.68841] \textit{Jang, Seok-Woo; El-Kwae, Essam A.; Choi, Hyung-Il}, Adaptive robust estimation for filtering motion vectors, 564-567 [Zbl 1013.68655] \textit{Lee, Seungkoo; Propes, Nicholas; Zhang, Guangfan; Zhao, Yongshen; Vachtsevanos, George}, Rough set feature selection and diagnostic rule generation for industrial applications, 568-571 [Zbl 1013.68891] \textit{Chen, Li}, \(\lambda\)-connected approximations for rough sets, 572-577 [Zbl 1013.68588] \textit{Nguyen, Tuan Trung}, Adaptive classifier construction: An approach to handwritten digit recognition, 578-585 [Zbl 1013.68534] \textit{Paszek, Piotr; Wakulicz-Deja, Alicja}, The application of support diagnose in mitochondrial encephalomyopathies, 586-593 [Zbl 1013.68860] \textit{Peters, James F.; Ahn, T. C.; Borkowski, Maciej}, Obstacle classification by a line-crawling robot: A rough neurocomputing approach, 594-601 [Zbl 1013.68247] \textit{Ramanna, Sheela}, Rough neural network for software change prediction, 602-609 [Zbl 1013.68598] \textit{Sinha, D.; Laplante, P.}, Handling spatial uncertainty in binary images: A rough set based approach, 610-620 [Zbl 1013.68583] \textit{Smolinski, Tomasz G.; Boratyn, Grzegorz M.; Milanova, Mariofanna; Zurada, Jacek M.; Wrobel, Andrzej}, Evolutionary algorithms and rough sets-based hybrid approach to classificatory decomposition of cortical evoked potentials, 621-628 [Zbl 1013.68527] \textit{Szmigielski, Adam}, Rough mereological localization and navigation, 629-637 [Zbl 1013.68616]
scientific article; zbMATH DE number 1839549