Storing a Sparse Table with 0(1) Worst Case Access Time
Journal of the ACM (JACM)
A scheme for constructing ordered minimal perfect hashing functions
Information Sciences: an International Journal
Dynamic Perfect Hashing: Upper and Lower Bounds
SIAM Journal on Computing
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient mining of traversal patterns
Data & Knowledge Engineering - Building web warehouse
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Using a Hash-Based Method with Transaction Trimming for Mining Association Rules
IEEE Transactions on Knowledge and Data Engineering
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
DEMON: Mining and Monitoring Evolving Data
IEEE Transactions on Knowledge and Data Engineering
Mining Sequential Patterns with Regular Expression Constraints
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Practical perfect hashing in nearly optimal space
Information Systems
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Hashing schemes are a common technique to improve the performance in mining not only association rules but also sequential patterns or traversal patters. However, the collision problem in hash schemes may result in severe performance degradation. In this paper, we propose perfect hashing schemes for mining traversal patterns to avoid collisions in the hash table. The main idea is to transform each large itemsets into one large 2-itemset by employing a delicate encoding scheme. Then perfect hash schemes designed only for itemsets of length two, rather than varied lengths, are applied. The experimental results show that our method is more than twice as faster than FS algorithm. The results also show our method is scalable to database sizes. One variant of our perfect hash scheme, called partial hash, is proposed to cope with the enormous memory space required by typical perfect hash functions. We also give a comparison of the performances of different perfect hash variants and investigate their properties.