Plenary Lecture

Todays’ Challenges in Text Mining

Professor Dzenana Donko
Faculty of Electrical Engineering
University of Sarajevo
Bosnia and Herzegovina
E-mail: ddonko@etf.unsa.ba

Abstract: Application of data mining methods is expanding. A huge amount of data is available in a variety of structured and unstructured forms. Available are also a variety of methods, algorithms and data mining tools that are useful for the specific analysis while not for the others. As part of this session methods for data mining with special attention to the text and web mining will be discussed. Text mining is using text documents as data in order to resolve problems such as: fast text search, text extraction and analysis for more languages, pattern recognitions in the books and papers in order to discover piracy, machine learning etc. The application and efficiency of data mining methods for different types of data mining will be illustrated through particular case studies. It will be identified and discussed problems related to different operations to transform text into the next step, which includes lexical analysis, stemming, identification of key terms and phrases and elimination of functional words.

Brief Biography of the Speaker: Dzenana Donko received M.Sc. degree in Computer Science from the University of Sarajevo, BiH at the Faculty of Electrical Engineering in 1991 and Ph.D. degree in Computer Science at the same University in 2004. She is currently an associated professor at the University of Sarajevo where she teaches various subjects on computer science. Besides being an author and co-author of numerous papers with special aspect of business intelligence and published book "Object Oriented Analysis and Design”, she is also member of the organizing committee and review of several international conferences. She was consultant on several projects for United Nations Development Project for digital government processes. Her research interest includes object oriented analysis and design, web architectures and web programming, workflow management, data mining, system analysis and design, and service management.