Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
In this paper, we show how Markovian strategies used to solve well-known segmentation problems such as motion estimation, motion detection, motion segmentation, stereovision, and c...
Extraction based Multi-Document Summarization Algorithms consist of choosing sentences from the documents using some weighting mechanism and combining them into a summary. In this...
The problem addressed in this work is to develop a comprehensive mathematical programming model for the efficient scheduling of oil-refinery operations. Our approach is first to d...