A Temporal Frequent Itemset-Based Clustering Approach For Discovering Event Episodes From News Sequence.
Yen-Hsien LeePaul Jen-Hwa HuTsai-Hsin ChuTsang-Hsiang ChengHsin-Wei ChenPublished in: PACIS (2011)
Keyphrases
- event sequences
- frequent itemsets
- temporal sequences
- itemsets
- temporal patterns
- frequent itemset mining
- news articles
- association rule mining
- mining algorithm
- clustering method
- temporal structure
- temporal information
- news stories
- event types
- frequent itemsets mining
- categorical data
- temporal order
- association rules
- data streams
- mining association rules
- discovery of association rules
- concise representation
- k means
- clustering algorithm
- data structure
- maximal frequent itemsets
- transaction databases
- itemset mining
- mining frequent itemsets
- cluster analysis
- emerging patterns
- topic detection
- transactional databases
- sequential patterns
- discovering frequent
- condensed representations
- frequent closed itemsets
- news events
- frequent patterns
- sequential data
- pattern mining
- frequent item sets
- minimum support
- graph mining