Text mining concerns applying data mining techniques to unstructured text. Information extraction (IE) is a form of shallow text understanding that locates specific pieces of data...
This paper presents a general framework for adapting any generative (model-based) clustering algorithm to provide balanced solutions, i.e., clusters of comparable sizes. Partition...
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
In this paper, we focus on mining periodic patterns allowing some degree of imperfection in the form of random replacement from a perfect periodic pattern. In InfoMiner+, we propo...
A lack of power and extensibility in their query languages has seriously limited the generality of DBMSs and hampered their ability to support data mining applications. Thus, ther...
A labeled sequence data set related to a certain biological property is often biased and, therefore, does not completely capture its diversity in nature. To reduce this sampling b...
Serial criminals are a major threat in the modern society. Associating incidents committed by the same offender is of great importance in studying serial criminals. In this paper,...
Conventional sequential pattern mining methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivi...
Hye-Chung Kum, Jian Pei, Wei Wang 0010, Dean Dunca...
We present two extensions of the algorithm by Broomhead et al [2] which is based on the idea that singular values that scale linearly with the radius of the data ball can be explo...