Janusz Sobecki

Using consensus methods to construct adaptive interfaces in multimodal web-based systems

This paper presents a concept of adaptive development of user interfaces in multimodal web-based systems. Today, it is crucial for general access web-based systems that the user interface is properly designed and adjusted to user needs and capabilities. It is believed that adaptive interfaces could offer a possible solution to this problem. Here, we introduce the notion of the user profile for classification, the interface profile for describing the system interface, and the compound usability measure for evaluation of the interface. Consensus-based methods are applied for constructing the interface profiles appropriate to classes of users.

Application of hybrid recommendation in web-based cooking assistant

The application of hybrid recommendation enables to overcome disadvantages of all three basic approaches: demographic, content-based, and collaborative ones. In this paper we present application of web-based cooking information system that recommends cooking recipes for different users. This work is continuation of previous works on hybrid recommendation that introduces application of fuzzy inference for demographic stereotype reasoning, which is the main new contribution of this paper.

Student courses recommendation using ant colony optimization

In the paper we present recommendation of student courses using Ant Colony Optimization (ACO). ACO is proved to be effective in solving many optimization problems, here we show that ACO also in the problem of prediction of final grades students receives on completing university courses is able to deliver good solutions. To apply ACO in any recommender system we need special problem representation in form of a graph, where each node represents a decision in the problem domain.

Ant Colony Metaphor Applied in User Interface Recommendation

In this paper web–based system user interface hybrid recommendation method based on the ant colony metaphor is presented. We apply the ontology–based user and user interface modeling. The user model is represented as a tuple and user interface model is represented by a set of connected nodes, what enables suitable user interface design, an interface personalization and recommendation. The recommendation is performed using ant colony metaphor for selection the most optimal path in the user interface graph that specifies the user interface parameters for the specified user.

Using eyetracking in a mobile applications usability testing

In this paper we present general problems of a mobile application usability testing by means of eyetracking. The motivation for considering this problem is the fact that eyetracking is still one of the most advanced usability testing tool. We achieved that by performing two eyetracking tests with the participation of users. We tested mobile application on smartphone and PC emulator, to find out which method gives the most valuable results. Both tests showed that eyetracking testing of mobile applications gives valuable results but to make it really efficient professional equipment designed for mobile eyetracking is required.

A model conception for optimal scenario determination in an intelligent learning system

In this paper a conception of the model for learning scenario determination is presented. We define the learning scenario as a sequence of the hypermedia pages, representing particular knowledge units, and tests related to them. The scenario determination is a dynamic process that begins when a new student takes up a course. The opening scenario for this student is chosen as the consensus of the final scenarios of the students, who have already finished this course, and who belong to a class of the learners similar to the new one. We have elaborated the consensus‐based procedure for the scenario determination. Since this procedure operates on a set of similar learners, we have developed the conceptions of learner’s profile and students’ classification. The learner’s profile is proposed to include the attributes describing students’ personal data (as name, birthday etc.), their cognitive and learning styles as well as their usage data (represented by the learning scenarios). The students’ classification is based on a set of the basic attributes that seem to influence the learning effects. Their significance is verified during the learning process. We have also elaborated the procedure of reducing undistinguishable values of the attribute and removing useless attributes from the set of basic attributes. A learning procedure proposed, describes generally the situations when the scenario is modified, and the methods used for its modification.

Smart work workbench; integrated tool for IT services planning, management, execution and evaluation

Smart Service Workbench (SSW) is an integrated tool devoted to support business processes in distributed IT environment based on Service Oriented Architecture (SOA) paradigm. The tools scope of functionalities is divided into modules that cover the whole process starting from the arrival of service request and ending with a return results of request. The latter is assumed to be a service composed of well-defined components available in predefined and staging repository. The tools modules are responsible for requirements analysis, services choice or service composition, communication and computational resources allocation in distributed environment as well as for resources utilization monitoring to services quality and security evaluation purposes.

Determination of user interfaces in adaptive systems using a rough classification-based method

This paper presents a novel method for user classification in adaptive systems based on rough classification. Adaptive systems could be used in many areas, for example in a user interface construction or e-Learning environments for learning strategy selection. In this paper the adaptation of web-based system user interface is presented. The goal of rough user classification is to select the most essential attributes and their values that group together users who are very much alike concerning the system logic. In order to group users we exploit their usage data taken from the user model of the adaptive web-based system user interface. We presented three basic problems for attribute selection that generates the following partitions: that is included, that includes and that is the closest to the given partition.

Hybrid Adaptation of Web-Based Systems User Interfaces

The interface adaptation is one of the methods for increasing the web-based system usability, especially when we consider differences among the population of users. We can distinguish demographic, content-based, and collaborative recommendations. The combination of these approaches that is called hybrid adaptation enables to overcome their disadvantages.

Consensus versus conflicts: methodology and applications

This paper is dedicated to applications of consensus methods in solving conflicts defined by Pawlak [12, 13]. The most characteristic feature of consensus methods surveyed in this paper is that the structures of opinions of conflict participants are multi-value and multiattribute and the basis of consensus determining consists of distance functions between tuples. In this work an overview of consensus methods and their applications in the scope of conflict solving is presented.