We propose a simple two-level hierarchical probability model for unsupervised word segmentation. By treating words as strings composed of morphemes/phonemes which are themselves c...
This paper is to investigate the group behavior patterns of search activities based on Web search history data, i.e., clickthrough data, to boost search performance. We propose a ...
Abstract. Implicit acquisition of user preferences makes log-based collaborative filtering favorable in practice to accomplish recommendations. In this paper, we follow a formal ap...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions...
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval f...