Sirmakessis S. (ed.) Text Mining and its Applications. Results of the NEMIS Launch Conference

Springer, 2004. — 207 p.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, casebased 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 unresolved. 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.The NEMIS project, funded by the IST framework, was set out to create a network of excellence (NoE), and bring together experts in the field of Text Mining to explore the grey areas relating to the status, trends and possible future developments in the technology, practices and uses of Text Mining.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.