Paweł Weichbroth

Cognitum Ontorion: Knowledge Representation and Reasoning System

At any point of human activity, knowledge and expertise are a key factors in understanding and solving any given problem. In present days, computer systems have the ability to support their users in an efficient and reliable way in gathering and processing knowledge. In this chapter we show how to use Cognitum Ontorion system in this areas. In first section, we identify emerging issues focused on how to represent and inference knowledge. Next, we briefly discuss models and methodology of agent-oriented system analysis and design. In the third section, the semantic knowledge management framework of the system is reviewed. Finally, we recapitulate by discussing the usability of Ontorion based on a case study, in which an instance of software process simulation modelling environment is executed and further discussed. In the last section, we provide future work directions and put forward final conclusions.

Exploring an Ontological Approach for User Requirements Elicitation in the Design of Online Virtual Agents

Effective user requirements elicitation is a key factor for the success of software development projects. There are many qualitative and quantitative research studies that promulgate particular methods and show the application of user requirements elicitation in particular domains. However, few try to eliminate the burden of ambiguity in gathered data, naturally occurring in different groups of stakeholders. This paper deals with this problem by introducing an ontology-based approach which by design provides a shared and common understanding of a domain. On the other hand, the developed ontology is a feasible communication facility for the stakeholders involved, acknowledged and controlled by a group of experts.

Towards better understanding of context-aware knowledge transformation

Considering different aspects of knowledge functioning, context is poorly understood in spite of intuitively identifying this concept with environmental recognition. For dynamic knowledge, context especially seems to be an essential factor of change. Investigation on the impact of context on knowledge dynamics or more generally on the relationship between knowledge and its contextual interpretation is important in order to understand knowledge dynamics. The aim of this paper is to research and examine the nature of knowledge transformation (a specific sort of life-cycle), and to identify contextual factors affecting knowledge dynamics.

Eye-tracking web usability research

In this paper we present the results of a study that aims to evaluate the usability of three selected web services, based on eye-tracking and thinking aloud techniques. The gathered comments and observations, recapitulated and supported by particular measures, allow us to discover and describe typical user behavior pertaining to given tasks to solve.

The lemniscate knowledge flow model

Knowledge is seen as one of the main resources for organizations providing knowledge-intensive services. Therefore, sharing and reusing are the main goals of the modern knowledge management (KM) approach, driven by information and communication technologies (ICT). However, one must ask for the details in order to provide the means and tools to design and deploy an environment able to fulfil these two goals. We observed that the interactions occurring on knowledge resources can be reduced to a directional flow, and further described by distinguished internal phases. In our research we put forward two research questions: (1) what are the main entities in the knowledge flow supported by ICT? and (2) what are the main phases of the knowledge flow? In this paper we introduce the generic lemniscate knowledge flow model, which, grounded on recognized theory, learned principles and gathered practices, provides foundations to solve the above problem.

Frequent Sequence Mining in Web Log Data

The amount of information available even on a single web server can be huge. On the other hand, the amount of visitors (users) can often reach a number of at least six digits. Users vary in gender, age and education, and in consequence their information needs are different. Moreover, they subconsciously expect to get more adequate content after visiting the first few pages. The scope of this kind of problem relates to the domain of information filtering, as a method for delivering relevant information. To solve such a problem, different sources of unstructured or structured data can be used, one of the latter type being web server log data. Executed logging processes on the server side can gather valuable data showing requests sent by users to available resources shared on a particular web site. In this paper, we introduce the Apriori-like FWP algorithm for frequent sequence mining in web log data. Discovered sequences present reconstructed navigation paths across shared web pages by a number of users satisfying a defined minimum. Such knowledge can primarily be used for content recommendation, as well as in cross-marketing strategies and email promotion campaigns.

Hard lessons learned: Delivering usability in IT projects

Effective project management requires the development of a realistic plan which aims to ensure the success of the project and ultimately deliver a high quality product to customers. However, experience shows that the majority of software vendors managing projects suffer from numerous problems to provide usability in IT solutions and complete a project in a given time with success. In this paper we discuss, analyze and synthesize the outcomes of a study conducted among IT firms in Poland. As a result, we have identified eight stimulants and three non-stimulants that affect the usability of software products, which later were stratified into three levels. Finally, we outline some of the lessons learned, summarized and expressed as a set of eleven goal-oriented rules.

Knowledge-Grid Modelling for Academic Purposes

Nowadays, we face a huge amount of data and information sharing on the Web by different users worldwide. A multidimensional perspective in describing a university ontology seems to be very important for the modelling of higher education resources. This paper proposes a multi-dimensional knowledge model, designed to distribute and manage knowledge resources efficiently. We propose our model as the foundation of an advanced knowledge platform including the following dimensions: time, area and social. Three crucial domains should be considered in this model: educational, research and managerial. The ontology including the mentioned knowledge management aspects is prepared using Ontorion Fluent Editor.