František Babič

The role of ontologies in collaborative systems

This paper deals with the role of ontologies in collaborative systems. The research field of collaborative systems and their support by information and communication technologies describes theory called CSCW (computer supported cooperative work). During last few years the CSCW has been evolving and extending, e.g. CSCL (computer supported collaborative learning) has emerged. With a well-defined ontology structure, CSCL can accumulate the knowledge representation of learning objects, including participant background, group information, instruction designs, learning activities and learning outcomes.

Meteorological phenomena forecast using data mining prediction methods

The occurrence of various meteorological phenomena, such as fog or low cloud cover, has significant impact on many human activities as air or ship transport operations. The management of air traffic at the airports was the main reason to design effective mechanisms for timely prediction of these phenomena. In both these cases meteorologists already use some physical models based on differential equations as simulations. Our goal was to design, implement and evaluate a different approach based on suitable techniques and methods from data mining domain. The selected algorithms were applied on obtained historical data from meteorological observations at several airports in United Arab Emirates and Slovakia. In the first case, the fog occurrence was predicted based on data from METAR messages with algorithms based on neural networks and decision trees. The low cloud cover was forecasted at the national Slovak airport in Bratislava with decision trees. The whole data mining process was managed by CRISP-DM methodology, one of the most accepted in this domain.

Analyses of Knowledge Creation Processes Based on Different Types of Monitored Data

This paper presents specialized methods for analyzing knowledge creation processes and knowledge practices that are (at least partially) projected in work within a virtual collaborative environment. Support for such analysis and evaluation of knowledge creation processes is provided by historical data stored in a virtual working environment, and describes various aspects of the monitored processes (e.g. semantic information, content, log of activities, etc.). The proposed analytical methods cover different types of analysis, such as (a) statistic analysis, that provides information about processes, and the possibility to visualize such information based on user-selected presentation modes; (b) time-line based analysis that supports visualization of the real process execution with all relevant information, including the possibility to identify and further analyze working patterns in knowledge creation processes (projection of knowledge practices). Experimental evaluation of the proposed methods is carried out within the IST EU project called KP-Lab.

On Patient’s Characteristics Extraction for Metabolic Syndrome Diagnosis: Predictive Modelling Based on Machine Learning

The work presented in this paper demonstrates how different data mining approaches can be applied to extend conventional combinations of variables determining the Metabolic Syndrome with new influential variables, which are easily available in the everyday physician‘s practice. The results have important consequences: patients with the Metabolic Syndrome can be recognized by using only some, one, or none of the conventional variables, when replaced with some other surrogate variables, available in patient health records, making diagnosis feasible in different work environments and at different time points of patient care. In addition, the results showed that there is a large diversity of patient groups, much larger than it was supposed earlier on when their identification was based on the conventional variables approach, indicating the underlying complexity of this syndrome. Finally, the discovered novel variables, indicating yet unknown pathogenetic pathways can be used to inspire future research.

Analytical Framework for Mirroring and Reflection of User Activities in E-Learning Environment

This chapter deals with evaluation of user activities and their participation in collaborative processes realized within the supporting virtual environment. The main goal behind proposed solution is to provide standalone package with all necessary functionalities to obtain data from examined virtual collaborative system in form of logs. For this purpose the following has been designed and implemented: a repository with predefined log format representing source historical data for analyzes; supporting middleware services for proposed analytical approaches; end-user tool for time-line based mirroring and analyses of user activities. These basic functionalities are extended with possibility to extract various summative statistics [10] about performed user activities and possibility to export data in predefined format (e.g. MS Excel) for analyses in third party tools as e.g. IBM SPSS Modeler. Described analytical framework has been designed, implemented and tested mainly within KP-Lab System that represents new interesting application in the domain of virtual environments or e-Learning systems. Proposed architecture was designed as generic platform with possibility to be integrated with other systems such as Moodle or Claroline in order to reflect different user practices.

Distributed task-based execution engine for support of text-mining processes

This paper describes design and implementation aspects for extension of our original software system developed in Java for support of information retrieval and text mining with specialized execution engine for different type of tasks. Some of our experiences and specific requirements of the real applications lead us to idea give the system possibility to run the tasks in distributive way. The result of the idea is task-based execution engine, which represents middleware-like transparent layer (mostly for programmers who want to re-use functionality of our package) for running of different tasks in multi-thread environment. The original system is being developed as open source with the intention to provide an easy extensible, modular framework for pre-processing, indexing and further exploration of large text collections. This specialized execution engine has been implemented within APVV project called PoZnaŤ (Support for knowledge creation processes) in order to extend proposed text-mining platform for educational and experimental purposes. Conceptual architecture of the system is provided as well as details regarding our extension of library like usage of content repository paradigm, representation and encapsulation of tasks, implementation of the engine itself and its role within PoZnaŤ platform.

Use of Semantic Principles in a Collaborative System in Order to Support Effective Information Retrieval

This paper focuses on information retrieval aspects of a new application in domain of collaborative systems based on utilization of semantic principles for representation of different types of knowledge, collaborative objects and relations between them. Proposed collaborative system (within European IST project called KP-Lab) uses ontologies as common communication framework and exchange format for different types of end-user tools. Theoretical background is provided by innovative theoretical approach called Trialogical learning. Information retrieval in KP-Lab System is supported by designed and implemented text-mining and search services. These two sets of functionalities provide features for management of shared objects, described with content in textual format, as well as with semantic metadata.

Simple understandable analysis of medical data to support the diagnostic process

Medical diagnostic is a complex process consisting of many input variables, which the general practitioner (GP) or specialist should take into account before confirm the expected diagnosis. In the case of electronic records, they have an opportunity to support this process within simple understandable results of the correctly applied suitable methods from machine learning or statistics. We used a small sample of patients data from Croatia for experimental evaluation of this potential. We applied the methods as Welchs t-test, Pearson chi-square independence test, Youdens index, decision trees and simple K-Means. The cooperating medical expert evaluated the obtained results and confirmed the expected potential for daily medical practice.

Analytical Platform Based on Jbowl Library Providing Text-Mining Services in Distributed Environment

The paper presents the Jbowl, Java software library for data and text analysis, and various research activities performed and implemented on top of the library. The paper describes the various analytical services for text and data mining implemented in Jbowl as well as numerous extensions aimed to address the evolving trends in data and text analysis and its usage in various tasks reflecting the areas such as big data analysis, distributed computing and parallelization. We also present the complex analytical platform built on top of the library, integrating the distributed computing analytical methods with the graphical user interface, visualization methods and resource management capabilities.

A new virtual environment for support and evaluation of various knowledge practices based on principles of trialogical learning

This paper presents a collaborative working and learning environment called KP-Lab System. It provides a complex and multifunctional application built on principles of Semantic Web, exploiting also some Web 2.0 approaches. This system offers virtual user environment with different, necessary and advanced features for collaborative learning or other knowledge intensive activities. This paper presents the whole system with special emphasis on its semantic-based aspects and analytical tools. Analytical tools were designed and implemented in order to provide various views on performed activities in user environment as summative statistics or time-line visualisation.