Some interesting papers I read in the past. Enjoy :-)
| Data Mining |
- Rakesh Agrawal, Ramakrishnan Srikant: Fast Algorithms for Mining Association Rules. VLDB'94
- Martin Ester, Hans-Peter Kriegel, Jorg Sander, Xiaowei Xu: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. KDD'96
- Wei Wang, Jiong Yang, Richard Muntz: STING : A Statistical Information Grid Approach to Spatial Data Mining . VLDB'97
- Rakesh Agrawal Johannes Gehrke Dimitrios Gunopulos Prabhakar Raghavan: Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. SIGMOD'98
- Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jorg Sander: OPTICS: Ordering Points To Identify the Clustering Structure. SIGMOD'99
- Charu C. Aggarwal, Philip S. Yu: Finding Generalized Projected Clusters in High Dimensional Spaces. SIGMOD'00
- Cecilia M. Procopiuc, Michael Jones: A Monte Carlo Algorithm for Fast Projective Clustering. SIGMOD'02
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| Data Privacy and Security |
- Daniel Kifer, Johannes Gehrke: Injecting Utility into Anonymized Datasets. SIGMOD'06
- Kristen LeFevre, David J. DeWitt, Raghu Ramakrishnan: Incognito: Efficient Full-Domain K-Anonymity. SIGMOD'05
- Rakesh Agrawal, Ramakrishnan Srikant, Dilys Thomas: Privacy Preserving OLAP. SIGMOD'05
- Charu C. Aggarwal: On k-Anonymity and the Curse of Dimensionality. VLDB'05
- Kristen LeFevre, David J. DeWitt, Raghu Ramakrishnan: Mondrian Multidimensional K-Anonymity.ICDE'06
- Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer, Muthuramakrishnan Venkitasubramaniam:
l-Diversity: Privacy Beyond k-Anonymity. ICDE'06
- Murat Kantarcioglu, Jiashun Jin, Chris Clifton: When do Data Mining Results Violate Privacy? KDD'04
- Jaideep Vaidya, Chris Clifton: Privacy-preserving k-means Clustering over Vertically Partitioned Data. KDD'03
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| Spatio-Temporal Databases |
- Tao, Y., Papadias, D. Time-Parameterized Queries in Spatio-Temporal Databases. SIGMOD'02
- Papadias, D., Zhang, J., Mamoulis, N., Tao, Y. Query Processing in Spatial Network Databases. VLDB'03
- Tao, Y., Papadias, D., Sun, J. The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries. VLDB'03
- Sun, J., Papadias, D., Tao, Y., Liu, B. Querying about the Past, the Present, and the Future in Spatio-Temporal Databases. ICDE'04
- Tao, Y., Faloutsos, C., Papadias, D., Liu, B. Prediction and Indexing of Moving Objects with Unknown Motion Patterns. SIGMOD'04
- Elias Frentzos: Indexing Objects Moving on Fixed Network
- Hyung-Ju Cho, Chin-Wan Chung: An Efficient and Scalable Approach to CNN Queries in a Road Network. VLDB'05
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| Data Warehousing and OLAP |
- Cuiping Li, Beng Chin Ooi, Anthony K. H. Tung, Shan Wang: DADA: A Data Cube for Dominant Relationship Analysis. SIGMOD'06
- Tian Xia, Donghui Zhang: Refreshing the Sky:The Compressed Skycube with Efficient Support for Frequent Updates. SIGMOD'06
- Chee Yong Chan, Pin-Kwang Eng, Kian-Lee Tan: Stratified Computation of Skylines with Partially-Ordered Domains. SIGMOD'05
- Jian Pei, Wen Jin, Martin Ester, Yufei Tao: Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces.VLDB'05
- Douglas Burdick, Prasad Deshpande, T. S. Jayram, Raghu Ramakrishnan, Shivakumar Vaithyanathan:
OLAP Over Uncertain and Imprecise Data. VLDB'05
- Yufei Tao, Xiaokui Xiao, Jian Pei: SUBSKY: Efficient Computation of Skylines in Subspaces. ICDE'06
- Iosif Lazaridis, Sharad Mehrotra: Progressive Approximate Aggregate Queries with a Multi-Resolution Tree Structure. SIGMOD'01
- Dimitrios Gunopulos, George Kollios, Vassilis J. Tsotras, Carlotta Domeniconi: Approximating Multi-Dimensional Aggregate Range Queries over Real Attributes. SIGMOD'00
- Jayavel Shanmugasundaram, Usama M. Fayyad, Paul S. Bradley: Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions. KDD'99
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| Unclassified |
- Hao Du, Yan Qiu Chen: Pattern Classification using Rectified Nearest Feature Line Segment. FSKD'05
- Peter Sanders, Dominik Schultes: Highway Hierarchies Hasten Exact Shortest Path Queries.
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