Keynote Lectures

Abstract: Data streams became ubiquitous as many sources produce data continuously and rapidly. Examples of streaming data include sensor networks, customer click streams, telephone records, web logs, multimedia data, sets of retail chain transactions, etc. These data sources are characterized by continuous generating huge amounts of data from non stationary distributions. Data Streams have brought new challenges to the data mining research community. In consequence, new techniques are needed to process streaming data in reasonable time and space. The goal of this talk is to present and discuss the research problems, issues and challenges in learning from data streams. We will present the state-of-the-art techniques and highlight applications of mining data streams in different domains.

 

 

Abstract: For many years, as a natural extension to their teaching activities and scientific research, the author and his team have been offering development of non-standard and complex software applications and information systems, and information technology related consultancy. They have experienced in their home country the communist times, time of war, transitional economy and finally the status of a country in European Union. Through all these times, optimization and/or software support to decision-making have been among their preferred tasks, often actively offered to users. During these years, a significant number of cases have demonstrated obstacles that were hindering this activity. The paper attempts an analysis of these obstacles, which are rarely clearly visible and nearly never explicitly expressed. Some of them may have become obsolete, although there is evidence in revered literature that in even the most developed economies similar wrong practices still exist. The reasons for obstacles principally may be located in wrong, insufficient or contrary motivation, in ignorance, and in natural resistance to any change. Motivating management practices can help in surmounting some of the obstacles.