The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
In this paper we discuss the important practical problem of customer wallet estimation, i.e., estimation of potential spending by customers (rather than their expected spending). ...
Claudia Perlich, Saharon Rosset, Richard D. Lawren...
We discuss the Innovation Jam that IBM carried out in 2006, with the objective of identifying innovative and promising "Big Ideas" through a moderated on-line discussion...
Wojciech Gryc, Mary E. Helander, Richard D. Lawren...
Abstract. Extracting information from very large collections of structured, semistructured or even unstructured data can be a considerable challenge when much of the hidden informa...
In analyzing data from social and communication networks, we encounter the problem of classifying objects where there is an explicit link structure amongst the objects. We study t...
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...