Great e orts have been paid in the Intelligent Database Systems Research Lab for the research and development of e cient data mining methods and construction of on-line analytical...
With over 800 million pages covering most areas of human endeavor, the World-wide Web is a fertile ground for data mining research to make a di erence to the e ectiveness of infor...
Knowledge discovery from data sets can be extensively automated by using data mining software tools. Techniques for mining series of interval events, however, have not been conside...
Roy Villafane, Kien A. Hua, Duc A. Tran, Basab Mau...
Data mining on large data warehouses is becoming increasingly important. In support of this trend, we consider a spectrum of architectural alternatives for coupling mining with da...
Mining frequent itemsets is at the core of mining association rules, and is by now quite well understood algorithmically for main memory databases. In this paper, we investigate a...
: In this paper we propose an application of data mining methods in the prediction of the availability and performance of Internet paths. We deploy a general decision-making method...
Abstract-- Mining textual documents and time series concurrently, such as predicting the movements of stock prices based on the contents of the news stories, is an emerging topic i...
Gabriel Pui Cheong Fung, Jeffrey Xu Yu, Hongjun Lu
Constraints are essential for many sequential pattern mining applications. However, there is no systematic study on constraint-based sequential pattern mining. In this paper, we in...
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...
We present an approach to enhancing information access through web structure mining in contrast to traditional approaches involving usage mining. Specifically, we mine the hardwi...