![]() ![]() ![]() | ![]() |
![]() ![]() ![]() ![]() ![]() |
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Note: Links lead to the DBLP on the Web. Christoph F. Eick Tae-Wan Ryu , Christoph F. Eick: A Systematic Database Summary Generation Using the Distributed Query Discovery System. ICCSA (4) 2004 : 185-195 Ricardo Vilalta , Murali-Krishna Achari , Christoph F. Eick: Class Decomposition via Clustering: A New Framework for Low-Variance Classifiers. ICDM 2003 : 673-676 X. Li , Christoph F. Eick: Fast Decision Tree Learning Algorithms for Microarray Data Collections. ICMLA 2003 : 37-43 Clifton Davis , Christoph F. Eick: A heuristic search based factoring tool. ICTAI 2000 : 298- Clifton Davis , Christoph F. Eick: Emperor: Cheap Legal Secure Cryptography for the Web. SAC 1999 : 603-609 Clifton Davis , Christoph F. Eick: Using Offset Invariant Crossover as a Tool for Discovering Cycle Lengths of a Periodic Function. Evolutionary Programming 1998 : 789-798 Ben S. Hadad , Christoph F. Eick: Supporting Polyploidy in Genetic Algorithms Using Dominance Vectors. Evolutionary Programming 1997 : 223-234 Ben S. Hadad , Christoph F. Eick: Using Recurrent Selection to Improve GA Performance. ISMIS 1997 : 247-256 Tae-Wan Ryu , Christoph F. Eick: Deriving Queries from Results Using Genetic Programming. KDD 1996 : 303-306 Yeong-Joon Kim , Christoph F. Eick: Multi-rule-set Decision-making Schemes for a Genetic Algorithm Learning Environment for Classification Tasks. Evolutionary Programming 1995 : 773-788 Christoph F. Eick, Yeong-Joon Kim , Nicola Secomandi : Enhancing Diversity for a Genetic Algorithm Learning Environment for Classfication Tasks. ICTAI 1994 : 820-823 Bogdan D. Czejdo , Bill P. Buckles , L. Smith , Christoph F. Eick: An Adaptive Browsing System Based on Rules for Object-Oriented Databases. IFIP Congress (1) 1994 : 121-126 Christoph F. Eick, Ema Toto : Evaluation and Enhancement of Bayesian Rule-Sets in a Genetic Algorithm Learning Environment for Classification Tasks. ISMIS 1994 : 366-375 Christoph F. Eick, Daw Jong : Learning Bayesian Classification Rules through Genetic Algorithms. CIKM 1993 : 305-313 Iliano Cervesato , Christoph F. Eick: Expression and Enforcement of Dynamic Integrity Constraints. SEBD 1993 : 283-298 Bogdan D. Czejdo , Christoph F. Eick, Malcolm C. Taylor : Integrating Sets, Rules, and Data in an Object-Oriented Environment. IEEE Expert 8 (1): 59-66 (1993) Christoph F. Eick, Paul Werstein : Rule-Based Consistency Enforcement for Knowledge-Based Systems. IEEE Trans. Knowl. Data Eng. 5 (1): 52-64 (1993) Bogdan D. Czejdo , Christoph F. Eick: Rules in an Extended C++. ICCI 1992 : 365-368 Sharon M. Tuttle , Christoph F. Eick: Suggesting Causes of Faults in Data-Driven Rule-Based Systems. ICTAI 1992 : 413-417 Bogdan D. Czejdo , Christoph F. Eick, Malcolm C. Taylor : TANGUY: Integrating Database, Rule-based and Object-Oriented Paradigms. DASFAA 1991 : 339-346 Christoph F. Eick: Integrating Variables and Operations into Rule-Based Forward Chaining Systems. ISMIS 1991 : 52-61 Christoph F. Eick: A Methodology for the Design and Transformation of Conceptual Schemas. VLDB 1991 : 25-34 Christoph F. Eick, Thomas Raupp : Toward a Formal Semantics and Inference Rules for Conceptual Data Models. Data Knowl. Eng. 6 : 297-317 (1991) Christoph F. Eick, Jia-Lin Liu , Paul Werstein : Integration of Rules into a Knowledge Base Management System. ICSI 1990 : 86-95 Christoph F. Eick, R. Kochhar , S. Kumar : DALI - a Knowledge Base Management System. IEA/AIE (Vol. 2) 1988 : 837-846 Christoph F. Eick, Peter C. Lockemann : Acquisition of Terminological Knowledge Using Database Design Techniques. SIGMOD Conference 1985 : 84-94 Christoph F. Eick: From Natural Language Requirements to good Data Base Definitions - A Data Base Design Methodology. ICDE 1984 : 324-331 Christoph F. Eick, Peter Raulefs : Problem Solving by Hyper Planning. AISB/GI (ECAI) 1978 : 103-104 1 [ 27 ] 2 [ 17 ] 3 [ 14 ] 4 [ 9 ] [ 11 ] [ 13 ] [ 17 ] 5 [ 23 ] [ 24 ] [ 25 ] 6 [ 21 ] [ 22 ] 7 [ 15 ] 8 [ 18 ] [ 19 ] 9 [ 4 ] 10 [ 4 ] 11 [ 26 ] 12 [ 5 ] 13 [ 3 ] 14 [ 1 ] 15 [ 6 ] 16 [ 20 ] [ 28 ] 17 [ 18 ] 18 [ 17 ] 19 [ 9 ] [ 13 ] 20 [ 16 ] 21 [ 10 ] 22 [ 27 ] 23 [ 5 ] [ 12 ] ![]() ©2004 Association for Computing Machinery |