The world of text mining is simultaneously a minefield and a gold mine. Text Mining is a rapidly developing applications field and an area of scientific research, using techniques from well-established scientific fields such as data mining, machine learning, information retrieval, natural language processing, case-based reasoning, statistics and knowledge management. The book contains the papers presented during the 1st International Workshop on Text Mining and its Applications held at the University of Patras, which was the launch event of the activities of NEMIS, a network of excellence in the area of text mining and its applications. The conference maintained a balance between theoretical issues and descriptions of case studies to promote synergy between theory and practice in the field of Text Mining. Topics of interest included document processing and visualization techniques, web mining, text mining and knowledge management, as well as user aspects and relations to official statistics

Klappentext

The world of text mining is simultaneously a minefield and a gold mine. It is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case­ based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain umesolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identified, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the field of Text Mining -especially in relation to IT- and whether there still remain areas to be covered.

Inhalt

Mining for Gems of Information.- From Text to Information: Document Processing and Visualization, a Text Mining Approach.- Web Mining: The Past, the Present, and Future.- Applications, Sectors and Strategies of Text Mining, a First Overall Picture.- Text Classification of News Articles with Support Vector Machines.- A Review of Web Document Clustering Approaches.- Supervised Term Weighting for Automated Text Categorization.- Machine Learning for Information Extraction in Genomics - State of the Art and Perspectives.- Processing Multilingual Collection for Text Mining Applications.- Text Mining Tools: Evaluation Methods and Criteria.- Knowledge Advantage through online Text Mining. Research Trends in Competitive Intelligence and Virtual Communities Applications.- Real Time Customer Opinion Monitoring.- Validation Techniques in Text Mining (with Application to the Processing of Open-ended Questions).- Clickstream Analysis, Semiotic Interpretation and Semantic Text Mining for a Distance Measurement on the Hypertextual Map of an Internet-portal.- Text Mining in Official Statistic.