Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diï...
While the task of answering queries from an arbitrary propositional theory is intractable in general, it can typicallybe performed e ciently if the theory is Horn. This suggests t...
In this paper, we study multiple target detection using Bayesian learning. The main aim of the paper is to present a computationally efficient way to compute the belief map update ...
When clustering a dataset, the right number k of clusters to use is often not obvious, and choosing k automatically is a hard algorithmic problem. In this paper we present an impr...