— Association Rule Mining is a thoroughly studied problem in Data Mining. Its solution has been aimed for by approaches based on different strategies involving, for instance, the...
Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association...
—The recent interest in outsourcing IT services onto the cloud raises two main concerns: security and cost. One task that could be outsourced is data mining. In VLDB 2007, Wong e...
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...
Abstract. In many contexts today, documents are available in a number of versions. In addition to explicit knowledge that can be queried/searched in documents, these documents also...
- The increase in autism prevalence has been the motivation for much research which has produced various theories for its causation. Genetic and environmental factors have been inv...
Christina Schweikert, Yanjun Li, David Dayya, Davi...
Temporal text mining deals with discovering temporal patterns in text over a period of time. A Theme Evolution Graph (TEG) is used to visualize when new themes are created and how...
Microarray datasets typically contain large number of columns but small number of rows. Association rules have been proved to be useful in analyzing such datasets. However, most e...
Gao Cong, Anthony K. H. Tung, Xin Xu, Feng Pan, Ji...
There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring and web click streams analysis. Different from data in t...
Breast cancer represents the second leading cause of cancer deaths in women today and it is the most common type of cancer in women. This paper presents some experiments for tumou...