Recommendation systems (RS) are important applications to help consumers to find
interesting products in large databases available on line. A wide range of RS can be easily …

The emerging of ubiquitous computing technologies in recent years has given rise to a new
field of research consisting in incorporating context-aware preference querying facilities in …

In this paper, we introduce a new problem, called Top-k SAT, that consists in enumerating
the Top-k models of a propositional formula. A Top-k model is defined as a model with less …

User preferences play an important role in database query personalization since they can
be used for sorting and selecting the objects which most fulfill the user wishes. In most …

In this article we propose CPrefMiner, a mining technique for learning a Bayesian
Preference Network (BPN) from a given sample of user choices. In our approach, user …

The extraction of knowledge and mining of useful dependencies represents a well
established class of tasks in data mining. Most of the algorithms devoted to this task …

The efficient and effective discovery of interesting information from data is an important
problem in many application and research domains. Presently, with the rapid development …

In this article, we present PrefRec, a general framework for developing RS using Preference
Mining and Preference Aggregation techniques. We focus on Pairwise Preference Mining …

针对在数据库的个性化查询中条件约束(或上下文约束) 没有被充分考虑的问题,
首先提出了条件约束模型i+≻ i-| X, 它表示在上下文X 的约束下, 相对于i-, 用户更偏好i+ …

Different preference mining techniques designed to predict a preference order on objects
have been proposed in the literature, with very good accuracy results. In this paper, we …