In this paper, a pattern-based stock data mining approach which transforms the numeric stock data to symbolic sequences, carries out sequential and non-sequential association analy...
Association rule mining is a popular task that involves the discovery of co-occurences of items in transaction databases. Several extensions of the traditional association rule mi...
KIM, JIHYE. Mining of Cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing. (Under the direction of Steffen Heber). Alternative splicing (AS) is an important...
Jihye Kim, Sihui Zhao, Brian E. Howard, Steffen He...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
We study the inference on the interesting association rules. Then we define the concept of the representative basis for interesting association rules extracted from a dataset D, a...