Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Bitmap index design and evaluation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
A performance comparison of bitmap indexes
Proceedings of the tenth international conference on Information and knowledge management
Measuring similarity of interests for clustering web-users
ADC '01 Proceedings of the 12th Australasian database conference
A Survey of Temporal Knowledge Discovery Paradigms and Methods
IEEE Transactions on Knowledge and Data Engineering
Association Rules... and What's Next? Towards Second Generation Data Mining Systems
ADBIS '98 Proceedings of the Second East European Symposium on Advances in Databases and Information Systems
Bitmap Indices for Speeding Up High-Dimensional Data Analysis
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
Presto Authorization: A Bitmap Indexing Scheme for High-Speed Access Control to XML Documents
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
A comparative study of signature based indexes for efficient retrieval of temporal patterns
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
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Data mining algorithms applied on the temporally sequenced data generate temporal patterns. A temporal pattern has a set of states and the temporal relationship among these states. When the number of generated patterns becomes large, it becomes essential to do post-processing of these patterns. The post-processing generally consists of storing the generated patterns in the database and later retrieving them by issuing content-based queries. In this paper, a novel method of indexing the database of temporal patterns is presented for efficient retrieval of selected patterns from a large database. The indexing technique proposed here, can handle the multiple states and relationships among the states of temporal patterns and retains the sequence among the states of the patterns. This new index structure, called Sequential Bitmap, is very efficient for content-based queries and shows significant improvements over the existing indexes.