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Note: Links lead to the DBLP on the Web. Martin Ester Rong She , Fei Chen , Ke Wang , Martin Ester, Jennifer L. Gardy , Fiona S. L. Brinkman : Frequent-subsequence-based prediction of outer membrane proteins. KDD 2003 : 436-445 Stefan Holland , Martin Ester, Werner Kießling : Preference Mining: A Novel Approach on Mining User Preferences for Personalized Applications. PKDD 2003 : 204-216 Benjamin C. M. Fung , Ke Wang , Martin Ester: Hierarchical Document Clustering using Frequent Itemsets. SDM 2003 Kai Yu , Xiaowei Xu , Martin Ester, Hans-Peter Kriegel : Feature Weighting and Instance Selection for Collaborative Filtering: An Information-Theoretic Approach*. Knowl. Inf. Syst 5 (2): 201-224 (2003) Jennifer L. Gardy , Cory Spencer , Ke Wang , Martin Ester, Gábor E. Tusnády , István Simon , Sujun Hua , Katalin de Fays , Christophe Lambert , Kenta Nakai , Fiona S. L. Brinkman : PSORT-B: improving protein subcellular localization prediction for Gram-negative bacteria. Nucleic Acids Research 31 (13): 3613-3617 (2003) Martin Ester, Hans-Peter Kriegel , Matthias Schubert : Web site mining: a new way to spot competitors, customers and suppliers in the world wide web. KDD 2002 : 249-258 Florian Beil , Martin Ester, Xiaowei Xu : Frequent term-based text clustering. KDD 2002 : 436-442 Kai Yu , Xiaowei Xu , Jianjua Tao , Martin Ester, Hans-Peter Kriegel : Instance Selection Techniques for Memory-based Collaborative Filtering. SDM 2002 Kai Yu , Xiaowei Xu , Martin Ester, Hans-Peter Kriegel : Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering. CIKM 2001 : 239-246 Kai Yu , Zhong Wen , Xiaowei Xu , Martin Ester: Feature Weighting Methods for Improving the Accuracy of Collaborative Filtering (Invited Address). DEXA Workshop 2001 : 285-290 Bernhard Braunmüller , Martin Ester, Hans-Peter Kriegel , Jörg Sander : Multiple Similarity Queries: A Basic DBMS Operation for Mining in Metric Databases. IEEE Trans. Knowl. Data Eng. 13 (1): 79-95 (2001) Bernhard Braunmüller , Martin Ester, Hans-Peter Kriegel , Jörg Sander : Efficiently Supporting Multiple Similarity Queries for Mining in Metric Databases. ICDE 2000 : 256-267 Martin Ester, Jörn Kohlhammer , Hans-Peter Kriegel : The DC-Tree: A Fully Dynamic Index Structure for Data Warehouses. ICDE 2000 : 379-388 Mihael Ankerst , Martin Ester, Hans-Peter Kriegel : Towards an effective cooperation of the user and the computer for classification. KDD 2000 : 179-188 Martin Ester, Alexander Frommelt , Hans-Peter Kriegel , Jörg Sander : Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support. Data Min. Knowl. Discov. 4 (2/3): 193-216 (2000) Martin Ester, Stefan Grundlach , Hans-Peter Kriegel , Jörg Sander : Database Primitives for Spatial Data Mining. BTW 1999 : 137-150 Martin Ester, Hans-Peter Kriegel , Jörg Sander : Knowledge Discovery in Spatial Databases. DAGM-Symposium 1999 : 1-14 Mihael Ankerst , Christian Elsen , Martin Ester, Hans-Peter Kriegel : Visual Classification: An Interactive Approach to Decision Tree Construction. KDD 1999 : 392-396 Martin Ester, Hans-Peter Kriegel , Jörg Sander : Knowledge Discovery in Spatial Databases. KI 1999 : 61-74 Martin Ester: Knowledge Discovery in Spatial Databases (Abstract). Datenbank Rundbrief 23 : 25 (1999) Mihael Ankerst , Christian Elsen , Martin Ester, Hans-Peter Kriegel : Perception-Based Classification. Informatica (Slovenia) 23 (4): (1999) Martin Ester, Rüdiger Wittmann : Incremental Generalization for Mining in a Data Warehousing Environment. EDBT 1998 : 135-149 Xiaowei Xu , Martin Ester, Hans-Peter Kriegel , Jörg Sander : A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases. ICDE 1998 : 324-331 Martin Ester, Alexander Frommelt , Hans-Peter Kriegel , Jörg Sander : Algorithms for Characterization and Trend Detection in Spatial Databases. KDD 1998 : 44-50 Martin Ester, Hans-Peter Kriegel , Jörg Sander , Michael Wimmer , Xiaowei Xu : Incremental Clustering for Mining in a Data Warehousing Environment. VLDB 1998 : 323-333 Jörg Sander , Martin Ester, Hans-Peter Kriegel , Xiaowei Xu : Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications. Data Min. Knowl. Discov. 2 (2): 169-194 (1998) Martin Ester, Hans-Peter Kriegel , Jörg Sander , Xiaowei Xu : Clustering for Mining in Large Spatial Databases. KI 12 (1): 18-24 (1998) Martin Ester, Hans-Peter Kriegel , Jörg Sander , Xiaowei Xu : Density-Connected Sets and their Application for Trend Detection in Spatial Databases. KDD 1997 : 10-15 Martin Ester, Hans-Peter Kriegel , Jörg Sander : Spatial Data Mining: A Database Approach. SSD 1997 : 47-66 Martin Ester, Hans-Peter Kriegel , Jörg Sander , Xiaowei Xu : A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. KDD 1996 : 226-231 Martin Ester, Hans-Peter Kriegel , Thomas Seidl , Xiaowei Xu : Formbasierte Suche nach komplementären 3D-Oberflächen in einer Protein-Datenbank. BTW 1995 : 373-382 Martin Ester, Hans-Peter Kriegel , Xiaowei Xu : A Database Interface for Clustering in Large Spatial Databases. KDD 1995 : 94-99 Martin Ester, Hans-Peter Kriegel , Xiaowei Xu : Knowledge Discovery in Large Spatial Databases: Focusing Techniques for Efficient Class Identification. SSD 1995 : 67-82 Hans-Jürgen Appelrath , Martin Ester, Heinrich Jasper , Alfred Ultsch : KOFIS: Ein Expertensystem zur integrierten Dokumenten- und Wissensverwaltung. Expertensysteme 1987 : 1-18 Hans-Jürgen Appelrath , Martin Ester: Integrity in a Knowledge Based Office Information System: Modeling with Extended SDM and Implementation with Prolog. Büroautomation 1985 : 172-191 1 [ 15 ] [ 18 ] [ 22 ] 2 [ 1 ] [ 2 ] 3 [ 29 ] 4 [ 24 ] [ 25 ] 5 [ 31 ] [ 35 ] 6 [ 35 ] 7 [ 15 ] [ 18 ] 8 [ 31 ] 9 [ 12 ] [ 21 ] 10 [ 33 ] 11 [ 31 ] [ 35 ] 12 [ 20 ] 13 [ 34 ] 14 [ 31 ] 15 [ 2 ] 16 [ 34 ] 17 [ 23 ] 18 [ 3 ] [ 4 ] [ 5 ] [ 6 ] [ 7 ] [ 8 ] [ 9 ] [ 10 ] [ 11 ] [ 12 ] [ 13 ] [ 15 ] [ 17 ] [ 18 ] [ 19 ] [ 20 ] [ 21 ] [ 22 ] [ 23 ] [ 24 ] [ 25 ] [ 27 ] [ 28 ] [ 30 ] [ 32 ] 19 [ 31 ] 20 [ 31 ] 21 [ 6 ] [ 7 ] [ 8 ] [ 9 ] [ 10 ] [ 11 ] [ 12 ] [ 13 ] [ 17 ] [ 19 ] [ 20 ] [ 21 ] [ 24 ] [ 25 ] 22 [ 30 ] 23 [ 5 ] 24 [ 35 ] 25 [ 31 ] 26 [ 31 ] 27 [ 28 ] 28 [ 31 ] 29 [ 2 ] 30 [ 31 ] [ 33 ] [ 35 ] 31 [ 26 ] 32 [ 11 ] 33 [ 14 ] 34 [ 3 ] [ 4 ] [ 5 ] [ 6 ] [ 8 ] [ 9 ] [ 10 ] [ 11 ] [ 13 ] [ 26 ] [ 27 ] [ 28 ] [ 29 ] [ 32 ] 35 [ 26 ] [ 27 ] [ 28 ] [ 32 ]  ©2004 Association for Computing Machinery |
