Distributed data mining in a chain store database of short transactions
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Market basket analysis in a multiple store environment
Decision Support Systems
Twain: Two-end association miner with precise frequent exhibition periods
ACM Transactions on Knowledge Discovery from Data (TKDD)
Efficient algorithms for incremental utility mining
Proceedings of the 2nd international conference on Ubiquitous information management and communication
Efficient algorithms for incremental Web log mining with dynamic thresholds
The VLDB Journal — The International Journal on Very Large Data Bases
Semantic-Based Temporal Text-Rule Mining
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
Mining Temporal Patterns for Humanoid Robot Using Pattern Growth Method
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Progressive weighted miner: an efficient method for time-constraint mining
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
An efficient algorithm for incremental mining of temporal association rules
Data & Knowledge Engineering
A three-scan algorithm to mine high on-shelf utility itemsets
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Discovery of high utility itemsets from on-shelf time periods of products
Expert Systems with Applications: An International Journal
Mining association rules in temporal document collections
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
An iterative method for mining frequent temporal patterns
EUROCAST'05 Proceedings of the 10th international conference on Computer Aided Systems Theory
A tree structure for event-based sequence mining
Knowledge-Based Systems
Web usage mining with evolutionary extraction of temporal fuzzy association rules
Knowledge-Based Systems
On-shelf utility mining with negative item values
Expert Systems with Applications: An International Journal
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In this paper, we explore a new problem of mining general temporal association rules in publication databases. In essence, a publication database is a set of transactions where each transaction T is a set of items of which each item contains an individual exhibition period. The current model of association rule mining is not able to handle the publication database due to the following fundamental problems, i.e., (1) lack of consideration of the exhibition period of each individual item; (2) lack of an equitable support counting basis for each item. To remedy this, we propose an innovative algorithm Progressive-Partition-Miner (abbreviatedly as PPM) to discover general temporal association rules in a publication database. The basic idea ofPPM is to first partition the publication database in light of exhibition periods of items and then progressively accumulate the occurrence count of each candidate 2-itemset based on the intrinsic partitioning characteristics. Algorithm PPM is also designed to employ a filtering threshold in each partition to early prune out those cumulatively infrequent 2-itemsets. Explicitly, the execution time of PPM is, in orders of magnitude, smaller than those required by the schemes which are directly extended from existing methods.