This article addresses Web personalization based on the analysis of individual user activity. However, human behavior is characterized by uncertainties that should be considered in the personalization algorithms. Fuzzy logic allows taking into account different types of uncertainty. Therefore, the paper presents a method for Web personalization based on fuzzy aggregation and recognition of user activity. The advantages of this approach are (1) the ability to use two types of fuzzy integrals without using the necessary expert set of fuzzy measures and (2) covering all stages of the personalization from aggregation of a single user’s query parameters to aggregation of an individual user’s profiles in a single parameter of group of users.
The rapid growth of computing devices has led to the emergence of distributed user interfaces. A user interface is called distributed if a user can interact with it using several devices at the same time. Formal methods for designing such interfaces, in particular methods for the distribution of interface elements across multiple devices, are yet to be developed. This is the reason why every time a new application requires a distributed user interface, the latter has to be designed from scratch, rendering the entire venture economically inefficient. In order to minimize costs, unify and automate the development of distributed interfaces, we need to formulate general formal methods for designing distributed interfaces that will be independent from a particular application or device. This article paper proposes a formal distribution method based on the pi-calculus.
A primary goal of virtual environments is to support natural, efficient, powerful and flexible human-computer interaction. But the traditional two-dimensional, keyboard- and mouse-oriented graphical user interface is not well-suited for virtual environments. The most popular approaches for capture, tracking and recognition of different modalities simultaneously to create intellectual human-computer interface for games will be considered in this chapter. Taking into account the large gesture variability and their important role in creating intuitive interfaces, the considered approaches focus one’s attention on gestures although the approaches may be used also for other modalities. The considered approaches are user independent and do not require large learning samples.
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