Building intelligent environment is one of crucial challenges for ubiquitous computing developers. To make the environment adapt rationally according to the desire of users, the system should be able to guess users’ interest, by learning users’ behavior, habit or preference. While learning the user preference, dealing with uncertainty and conflict resolution is of the utmost importance. When ma...

With personalisation becoming more prevalent, it can often be useful to be able to infer additional preferences from input user preferences. Preference inference techniques assume a set of possible user preference models, and derive inferences that hold in all models satisfying the inputs; the more restrictive one makes the set of possible user preference models, the more inferences one gets. S...

Due to the problem of data heterogeneity in semantic sensor networks, communications among different network applications are seriously hampered. Although ontology is regarded as state-of-the-art knowledge model for exchanging information, there also exists between ontologies. Ontology matching an effective method deal with problem, whose kernel technique similarity measure. How integrate measu...

Personalized news article recommendation provides interesting articles to a specific user based on the preference of the user. With increasing use of hand-held devices, the interests of users are not influenced only by news contents, but also by their location. Therefore, in this paper, we propose a novel topic model to incorporate user location into a user preference for the location-based per...

As ubiquitous commerce is coming, the ubiquitous recommendation systems utilize collaborative filtering to help users with fast searches for the best suitable items by analyzing the similar preference. However, collaborative filtering may not provide high quality recommendation because it does not consider user’s preference on the attribute, the first rater problem, and the sparsity problem. Th...

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 database systems. One important step in this setting is the Preference Elicitation task which consists in providing the user ways to inform his/her choice on pairs of objects with a minimal effort. In this paper w...

Nowadays websites provide a vast number of resources for users. Recommender systems have been developed as an essential element of these websites to provide a personalized environment for users. They help users to retrieve interested resources from large sets of available resources. Due to the dynamic feature of user preference, constructing an appropriate model to estimate the user preference ...

Users make choices among multi-attribute objects in a data set in a variety of domains including used car purchase, job search and hotel room booking. Individual users sometimes have strong preferences between objects, but these preferences may not be universally shared by all users. If we can cast these preferences as derived from a quantitative user-specific preference function, then we can p...