Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Recommender systems are used by an increasing number of e-commerce websites to help the customers to find suitable products from a large database. One of the most popular techniqu...
Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thiem...
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
In the typical nonparametric approach to classification in instance-based learning and data mining, random data (the training set of patterns) are collected and used to design a d...
Binay K. Bhattacharya, Kaustav Mukherjee, Godfried...
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...