The increasing variety of mobile multimedia services raises the need for mechanisms to select those services whose capabilities best match individual user requirements. In this paper we present an advanced concept for service personalization in next-generation IP-based mobile systems based on the notion of user preferences. The described concept features several enhancements for personalization...

The increasing variety of mobile multimedia services raises the need for mechanisms to select those services whose capabilities best match individual user requirements. In this paper, we present an advanced concept for service personalization in next-generation IP-based mobile systems based on the notion of user preferences. The described concept features several enhancements for personalizatio...

We consider soft constraint problems where some of the preferences may be unspecified. This models, for example, settings where agents are distributed and have privacy issues, or where there is an ongoing preference elicitation process. In this context, we study how to find an optimal solution without having to wait for all the preferences. In particular, we define algorithms, that interleave s...

Models of user preferences are an important resource to improve the user experience of recommender systems. Using user feedback static preference models can be adapted over time. Still, if the options to choose from themselves have temporal extent, dynamic preferences have to be taken into account even when answering a single query. In this paper we propose that static preference models could b...

Current models for document summarization ignore user preferences such as the desired length, style or entities that the user has a preference for. We present a neural summarization model that enables users to specify such high level attributes in order to control the shape of the final summaries to better suit their needs. With user input, we show that our system can produce high quality summa...

A Conversational Recommender System(CRS) aims to simulate the real world setting where a shopkeeper tries to learn the preferences of a user through conversation and the user, in turn, learns about the product base. Often the preference of the user is captured in the form of feature weights and they are updated assuming each feature is independent. These feature weights are used in product retr...

Social Annotation Systems have emerged as a popular application with the advance of Web 2.0 technologies. Tags generated by users using arbitrary words to express their own opinions and perceptions on various resources provide a new intermediate dimension between users and resources, which deemed to convey the user preference information. Using clustering for topic extraction and incorporating ...

One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two conflicting objectives (i.e., accuracy maximization and complexity minimization) when we design accurate and compact fuzzy rule-based systems from numerical data. Since the main advantage of fuzzy rule-based systems co...

We describe our ongoing research into gesture as an interaction technique for ubiquitous and pervasive computing. The goal of our research is to, 1. identify, through studies on user generated gestures, a gesture set for ubiquitous and pervasive computing which is both useful and useable across a range of devices, services and contexts 2. apply this gesture set to a range of gesture recognition...