Most approaches to topic modeling assume an independence between documents that is frequently violated. We present an topic model that makes use of one or more user-specified grap...
Abstract. We consider the problem of learning a user's ordinal preferences on a multiattribute domain, assuming that her preferences are lexicographic. We introduce a general ...
The paper presents a new kind of fuzzy binary relations for modelling conditional possibility. The key idea is to consider fuzzy preorders as conditional necessity measures, and t...
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
Documents in many corpora, such as digital libraries and webpages, contain both content and link information. To explicitly consider the document relations represented by links, i...