Abstract— In previous work, we have shown that both unsupervised feature selection and the semi-supervised clustering problem can be usefully formulated as multiobjective optimiz...
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
In semi-supervised clustering, domain knowledge can be converted to constraints and used to guide the clustering. In this paper we propose a feature selection algorithm for semi-s...
This paper presents an unsupervised texture segmentation method, which uses distributions of local binary patterns and pattern contrasts for measuring the similarity of adjacent i...
Abstract. Training data as well as supplementary data such as usagebased click behavior may abound in one search market (i.e., a particular region, domain, or language) and be much...