Intelligent human-device interfaces play key roles in fully automated vehicles (FAVs), ensuring smooth interactions and improving the driving experience. Listening to news is a popular method of relaxing during journey; as result, travelers require automatic recommendations preferred programs. Most existing recommender systems usually learn topic-level representations users for while neglecting...

Visual aesthetics is vital in determining the usability of graphical user interface (GUI). It can strengthen competitiveness interactive online applications. Human aesthetic preferences for GUI are implicit and linked to various aspects perception. In this study, an image database was constructed with 38,423 design works collected from Huaban.com, a popular social network website art sharing, c...

The handling of user preferences is becoming an increasingly important issue in present-day information systems. Among others, preferences are used for information filtering and extraction to reduce the volume of data presented to the user. They are also used to keep track of user profiles and formulate policies to improve and automate decision making. We propose here a simple, logical framewor...

Elicitation and validation of user requirements depend, to a large extent, on the effectiveness of the tools and techniques used as a vehicle for discussion between developers and users during the requirements process. This effectiveness may, in turn, be influenced by user preference for a particular approach or requirements technique. This paper describes a study that was carried out to invest...

Bayesian approaches to preference elicitation (PE) are particularly attractive due to their ability to explicitly model uncertainty in users’ latent utility functions. However, previous approaches to Bayesian PE have ignored the important problem of generalizing from previous users to an unseen user in order to reduce the elicitation burden on new users. In this paper, we address this deficienc...

For mobile telecom operators, it is critical to build preference profiles of their customers and connected users, which can help operators make better marketing strategies, and provide more personalized services. With the deployment of deep packet inspection (DPI) in telecom networks, it is possible for the telco operators to obtain user online preference. However, DPI has its limitations and u...

We investigate the solution of constraint-based configuration problems in which the preference function over outcomes is unknown or incompletely specified. The aim is to configure a system, such as a personal computer, so that it will be optimal for a given user. The goal of this project is to develop algorithms that generate the most preferred feasible configuration by posing preference querie...

The integration of SaaS service for group user in cloud is challenging, notably because the service’s QoS and member’s personalization QoS preference in group are uncertain. This is a timely and importance problem with the advent of the SaaS model of service delivery. Therefore, before the SaaS service been utilized, the service alternatives must be ranked for group user based on services’ QoS ...

By using relevance feedback [6], Content -Based Image Retrieval (CBIR) allows the user to retrieve images interactively. Begin with a coarse query , t he user can select the most relevant images and provide a weight of preference for each relevant image to refine the query . The high level concept borne by the user and perception subjectivity of the user can be automatically captured by the sys...

We propose a hybrid learning approach to provide automated assistance for personalized product recommendation. The novel feature of this work is that the system learns and uses models of both user preferences and the user’s intentional context. Both learning types are based on the same user input, but elicit different aspects of the user model. User preference is learned via Support Vector Mach...