User preferences

Larger display surfaces are becoming increasingly available due to multi-monitor capability built into many systems, in addition to the rapid decrease in their costs. However, little is known about the performance benefits of using these larger surfaces compared to traditional single-monitor displays. In addition, it is not clear that current software designs and interaction techniques have been properly tuned for

Sensory innovation in the flavor industry is a pro- cess that relies heavily on user involvement to carry out critical sampling trials at a high cost. We are interested in how recommender systems, in par- ticular, have an important role to play in view of addressing some of their key challenges and con- straints. We describe a purpose-built sensory rec-

As proved by the continuous growth of the number of web sites which embody recommender systems as a way of personalizing the experience of users with their content, recommender systems represent one of the most popular applications of principles and techniques com- ing from Information Filtering (IF). As IF techniques usually perform a progressive removal of non-relevant content according to

Our research agenda focuses on building software agents that can employ user modeling techniques to facilitate information access and management tasks. Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems, can be used to recommend items of interest to users. To be successful, such systems should be able to

... For example, tourists need indoor navigation services in some large museums to see the artifacts in different places in sequence. In addition, posi-tion information brings benefits to self-organization and self-formation of ad hoc networks in the future communications systems. ...

The vast amount of heterogeneous information sources available on the Internet demands advanced solutions for acquiring, mediating, and maintaining relevant information for the common user. Intelligent information agents are autonomous computational software entities that are especially meant to (1) provide pro-active resource discovery, (2) resolve information impedance of information consumers and providers, and (3) offer value-added information services and products. These agents are supposed to cope with the difficulties associated with the information overload of the user, preferably just in time.Based on a systematic classification of intelligent information agents, this paper presents an overview of the basic key enabling technologies needed to build such agents, and respective examples of information agent systems currently deployed on the Internet.

Operating systems and programmes are more protected these days and attackers have shifted their attention to human elements to break into the organisation's information systems. As the number and frequency of cyber-attacks designed to take advantage of unsuspecting personnel are increasing, the significance of the human factor in information security management cannot be understated. In order to counter cyber-attacks designed

Over the past two decades, great research efforts have been made towards the personalization of e-learning platforms. This feature increases remarkably the quality of the provided learning services, since the users’ special needs and capabilities are respected. The idea of predicting the users’ preferences and adapting the e-learning platform accordingly is the focal point of this paper. In particular, this paper starts with the main requirements of an advanced e-learning system, explains the way a user navigates in such a system, presents the architecture of a corresponding e-learning system and describes its main components. Research is focused on the User Model component, its role in the e-learning system and the parameters that comprise it. In this context, Bayesian Networks are used as a tool for the encoding, learning and reasoning of probabilistic relationships, with the aim to effectively predict user preferences. In support of this vision, four different scenarios are presented, in order to test the way Bayesian Networks apply in the e-learning field.

During the last decades, digital media have revolutionised media reproduction. The availability of cheap consumer electronic devices that allow the consumption and management of digital multimedia content (eg MP3 players, digital cameras, DV camcorders, smart phones) has caused a media availability explosion. The amount of digital media that has been generated and stored, and which continues to be at an exponential rate, has already become unmanageable without fine-grained computerised support.

The objective of this study was to investigate and report on user preference of natural search results, thus search engine optimisation (SEO), versus pay per click (PPC) results. This will assist online advertisers to identify their optimal search engine marketing (SEM) strategy for their specific target market. Research shows that online advertisers perceive PPC as a more effective SEM strategy than SEO. However, empirical evidence exists that PPC may not be the best SEM strategy for online advertisers. Not all advertisers have the funds to implement a dual SEM strategy and therefore advertisers need to choose between a PPC and SEO campaign. In order for online advertisers to choose the most relevant SEM strategy, it is crucial to understand user perceptions of SEM strategies. A quantitative research design was used to conduct this study, with the purpose to collect and analyze data. A questionnaire was designed and placed on a website for gathering data. The questionnaire focused on how search engine users perceive SEM and their click response towards PPC and SEO respectively. The data was analysed and the results inspected. Results showed that the user perceived relevancy split is roughly 40%-60% (PPC results to SEO results), regardless of demographic factors. This indicates that websites should invest in both PPC and SEO. Failing to invest in either one could cause a significant loss of traffic. For websites that can not afford a dual SEM strategy, advertisers should correlate the results of this study with their target market to establish their optimal SEM strategy, or invest in SEO as results showed more users click through on SEO results than on PPC results.