Skip header Section
Skip Bibliometrics Section
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software SystemsOctober 1998
- Editors:
- Lech Polkowski,
- J. Kacprzyk,
- A. Skowron
Abstract
No abstract available.
Cited By
- Efendi R, Mu'at S, Arisandi N and Samsudin N Removing Unclassified Elements in Investigating of Financial Wellbeing Attributes Using Rough-Regression Model Proceedings of the 2019 8th International Conference on Software and Computer Applications, (87-90)
- Li Y, Wu S, Lin Y and Liu J (2017). Different classes' ratio fuzzy rough set based robust feature selection, Knowledge-Based Systems, 120:C, (74-86), Online publication date: 15-Mar-2017.
- Lu J, Zheng Z, Zhang G, He Q and Shi Z (2015). A new solution algorithm for solving rule-sets based bilevel decision problems, Concurrency and Computation: Practice & Experience, 27:4, (830-854), Online publication date: 25-Mar-2015.
- (2014). Graph and matrix approaches to rough sets through matroids, Information Sciences: an International Journal, 288:C, (1-11), Online publication date: 20-Dec-2014.
- An S, Hu Q and Yu D Case-based classifiers with fuzzy rough sets Proceedings of the 6th international conference on Rough sets and knowledge technology, (172-177)
- An S, Hu Q and Yu D A robust fuzzy rough set model based on minimum enclosing ball Proceedings of the 5th international conference on Rough set and knowledge technology, (102-109)
- Liu G and Zhu W (2010). Approximations in Rough Sets vs Granular Computing for Coverings, International Journal of Cognitive Informatics and Natural Intelligence, 4:2, (63-76), Online publication date: 1-Apr-2010.
- Wang W and Mi H The application of rough neural network in RMF model Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1, (210-213)
- Tsang E and Suyun Z Decision table reduction in KDD Transactions on Rough Sets XI, (177-188)
- Gomolińska A Satisfiability judgement under incomplete information Transactions on Rough Sets XI, (66-91)
- Delimata P, Marszał-Paszek B, Moshkov M, Paszek P, Skowron A and Suraj Z Comparison of some classification algorithms based on deterministic and nondeterministic decision rules Transactions on rough sets XII, (90-105)
- Mohanty D (2019). Covering based approximation – a new type approach, International Journal of Computational Vision and Robotics, 1:3, (335-345), Online publication date: 1-Jan-2010.
- Shi H Bid/no-bid decision-making using rough sets and neural networks Proceedings of the 21st annual international conference on Chinese control and decision conference, (6105-6109)
- Sakai H, Ishibashi R, Koba K and Nakata M Rules and Apriori Algorithm in Non-deterministic Information Systems Transactions on Rough Sets IX, (328-350)
- Leoreanu-Fotea V and Davvaz B (2008). Roughness in n-ary hypergroups, Information Sciences: an International Journal, 178:21, (4114-4124), Online publication date: 1-Nov-2008.
- Fotea V (2008). The lower and upper approximations in a hypergroup, Information Sciences: an International Journal, 178:18, (3605-3615), Online publication date: 20-Sep-2008.
- Chen D, Yang W and Li F (2008). Measures of general fuzzy rough sets on a probabilistic space, Information Sciences: an International Journal, 178:16, (3177-3187), Online publication date: 1-Aug-2008.
- Sun B, Gong Z and Chen D (2019). Fuzzy rough set theory for the interval-valued fuzzy information systems, Information Sciences: an International Journal, 178:13, (2794-2815), Online publication date: 1-Jul-2008.
- Tsang E, Degang C and Yeung D (2008). Approximations and reducts with covering generalized rough sets, Computers & Mathematics with Applications, 56:1, (279-289), Online publication date: 1-Jul-2008.
- Leung Y, Fischer M, Wu W and Mi J (2008). A rough set approach for the discovery of classification rules in interval-valued information systems, International Journal of Approximate Reasoning, 47:2, (233-246), Online publication date: 1-Feb-2008.
- Elhadi M and Ziarko W A rough sets approach to the identification and analysis of factors affecting biological control of leafy spurge Transactions on rough sets VIII, (75-92)
- Peters J Toward Approximate Adaptive Learning Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms, (57-68)
- Sammany M and Medhat T Dimensionality Reduction Using Rough Set Approach for Two Neural Networks-Based Applications Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms, (639-647)
- Synak P and ńlezak D Descriptors and templates in relational information systems Proceedings of the 2nd international conference on Rough sets and knowledge technology, (403-410)
- Peters J Near sets Proceedings of the 2nd international conference on Rough sets and knowledge technology, (22-33)
- Peters J (2007). Near Sets. Special Theory about Nearness of Objects, Fundamenta Informaticae, 75:1-4, (407-433), Online publication date: 1-Jan-2007.
- Zhu W Properties of the Second Type of Covering-Based Rough Sets Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology, (494-497)
- Synak P and Ślezak D Tolerance based templates for information systems Proceedings of the 1st international conference on Advances in hybrid information technology, (11-19)
- Yamaguchi D, Li G and Nagai M On the combination of rough set theory and grey theory based on grey lattice operations Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing, (507-516)
- Li G, Yamaguchi D, Lin H, Wen K and Nagai M A grey-based rough set approach to suppliers selection problem Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing, (487-496)
- Mitra S, Mitra M and Chaudhuri B An approach to a rough set based disease inference engine for ECG classification Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing, (398-407)
- Bazan J, Latkowski R and Szczuka M Missing template decomposition method and its implementation in rough set exploration system Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing, (254-263)
- Zhu W and Wang F Binary relation based rough sets Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery, (276-285)
- Polkowski L Rough mereological reasoning in rough set theory Proceedings of the First international conference on Rough Sets and Knowledge Technology, (79-92)
- Peters J and Skowron A Zdzisław pawlak Transactions on Rough Sets V, (1-24)
- Zheng Z, Zhang G, He Q, Lu J and Shi Z Rule sets based bilevel decision model Proceedings of the 29th Australasian Computer Science Conference - Volume 48, (113-120)
- Sakai H, Murai T and Nakata M On a tool for rough non-deterministic information analysis and its perspective for handling numerical data Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence, (203-214)
- Tsumoto S Statistical independence from the viewpoint of linear algebra Proceedings of the 15th international conference on Foundations of Intelligent Systems, (56-64)
- Hassan Y and Tazaki E Emergent rough set data analysis Transactions on Rough Sets II, (343-361)
- Sakai H Possible equivalence relations and their application to hypothesis generation in non-deterministic information systems Transactions on Rough Sets II, (82-106)
- Suraj Z and Grochowalski P The rough set database system Transactions on Rough Sets III, (190-201)
- Peters J Rough ethology Transactions on Rough Sets III, (153-174)
- Shen L and Loh H (2004). Applying rough sets to market timing decisions, Decision Support Systems, 37:4, (583-597), Online publication date: 1-Sep-2004.
- Gomolińska A (2019). A Graded Meaning of Formulas in Approximation Spaces, Fundamenta Informaticae, 60:1-4, (159-172), Online publication date: 1-Jan-2004.
- Gomolińska A (2019). A Graded Meaning of Formulas in Approximation Spaces, Fundamenta Informaticae, 60:1-4, (159-172), Online publication date: 1-Sep-2003.
- Wieczorkowska A, Wróblewski J, Synak P and Ślȩzak D (2019). Application of Temporal Descriptors to Musical Instrument Sound Recognition, Journal of Intelligent Information Systems, 21:1, (71-93), Online publication date: 1-Jul-2003.
- Peters J, Skowron A, Synak P and Ramanna S Rough sets and information granulation Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems, (370-377)
- Tsumoto S Characteristics of accuracy and coverage in rule induction Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, (237-244)
- Bazan J, Son N, Skowron A and Szczuka M A view on rough set concept approximations Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, (181-188)
- Yao Y, Zhao Y and Maguire R Explanation oriented association mining using rough set theory Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, (165-172)
- Skowron A and Peters J Rough sets Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing, (25-34)
- Nguyen H and Nguyen S Approximated measures in construction of decision trees from large databases Design and application of hybrid intelligent systems, (595-604)
- Pawlak Z (2002). Rough sets and intelligent data analysis, Information Sciences: an International Journal, 147:1-4, (1-12), Online publication date: 1-Oct-2002.
- Zhao K and Wang J (2002). A reduction algorithm meeting users’ requirements, Journal of Computer Science and Technology, 17:5, (578-593), Online publication date: 1-Sep-2002.
- Şlȩzak D (2002). Approximate entropy reducts, Fundamenta Informaticae, 53:3,4, (365-390), Online publication date: 30-May-2002.
- Gomolińska A (2002). A comparative study of some generalized rough approximations, Fundamenta Informaticae, 51:1, (103-119), Online publication date: 15-Mar-2002.
- Tsumoto S Medicine Handbook of data mining and knowledge discovery, (798-807)
- Pedrycz W and Skowron A Fuzzy and rough sets Handbook of data mining and knowledge discovery, (680-689)
- Komorowski J, Øhrn A and Skowron A Case studies: Public domain, multiple mining tasks systems Handbook of data mining and knowledge discovery, (554-559)
- Ziarko W Data mining tasks and methods: Rule discovery Handbook of data mining and knowledge discovery, (328-339)
- Gomolińska A (2019). A Comparative Study of Some Generalized Rough Approximations, Fundamenta Informaticae, 51:1-2, (103-119), Online publication date: 1-Jan-2002.
- Nguyen H (2019). On Efficient Handling of Continuous Attributes in Large Data Bases, Fundamenta Informaticae, 48:1, (61-81), Online publication date: 30-Oct-2001.
- Zhong N, Dong J and Ohsuga S (2019). Using Rough Sets with Heuristics for Feature Selection, Journal of Intelligent Information Systems, 16:3, (199-214), Online publication date: 5-Oct-2001.
- Nguyen H (2019). On Efficient Handling of Continuous Attributes in Large Data Bases, Fundamenta Informaticae, 48:1, (61-81), Online publication date: 1-Jan-2001.
- Siromoney A and Inoue K (2019). Consistency and Completeness in Rough Sets, Journal of Intelligent Information Systems, 15:3, (207-220), Online publication date: 1-Nov-2000.
- Kawasaki S, Nguyen N and Ho T Hierarchical Document Clustering Based on Tolerance Rough Set Model Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery, (458-463)
- Tsumoto S Clinical Knowledge Discovery in Hospital Information Systems Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery, (652-656)
Please enable JavaScript to view thecomments powered by Disqus.
Recommendations
Relationships between covering-based rough sets and relation-based rough sets
Rough set theory is an important technique to deal with vagueness and granularity in information systems. In rough set theory, relation-based rough sets and covering-based rough sets are two important extensions of the classical rough sets. This paper ...
Soft rough fuzzy sets and soft fuzzy rough sets
Fuzzy set theory, soft set theory and rough set theory are mathematical tools for dealing with uncertainties and are closely related. Feng et al. introduced the notions of rough soft set, soft rough set and soft rough fuzzy set by combining fuzzy set, ...
Multigranulation decision-theoretic rough sets
The Bayesian decision-theoretic rough sets propose a framework for studying rough set approximations using probabilistic theory, which can interprete the parameters from existing forms of probabilistic approaches to rough sets. Exploring rough sets in ...