Text Mining in Action!

Text mining methods have being successfully used on different problems, where text data is involved. Some Text mining approaches are capable of handling text just relying on statistics such as, frequency of words or phrases, while others assume availability of additional resources such as, natural language processing tools for the language in which the text is written; availability of lexicons; ontologies of concepts; aligned corpus in several languages; additional data sources such as, links between the text units or other non-textual data. This paper aims at illustrating potential of Text mining by presenting several approaches having some of the listed properties. For this purpose, we present research applications that were developed mainly inside European projects in collaboration with end-users and, research prototypes that do not necessary involve end-users.

[1]  Dunja Mladenic.  Web Browsing Using Machine Learning on Text Data , 2003, Intelligent Exploration of the Web.

[2]  Dunja Mladenic,et al.  Feature selection on hierarchy of web documents , 2003, Decis. Support Syst..

[3]  Samuel Kaski,et al.  Self organization of a massive document collection , 2000, IEEE Trans. Neural Networks Learn. Syst..

[4]  Dunja Mladenic,et al.  Data mining and decision support : integration and collaboration , 2003 .

[5]  Lucy T. Nowell,et al.  ThemeRiver: visualizing theme changes over time , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[6]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[7]  Dunja Mladenic,et al.  Web Site Access Analysis for a National Statistical Agency , 2003 .

[8]  Dunja Mladenic,et al.  Web Mining: From Web to Semantic Web: First European Web Mining Forum, EWMF 2003, Cavtat-Dubrovnik, Croatia, September 22, 2003, Revised Selected and Invited Papers (Lecture Notes in Computer Science) , 2004 .

[9]  Dunja Mladenic,et al.  Efficient Visualization of Large Text Corpora , 2002 .

[10]  Dunja Mladenic,et al.  Analysis of a Database of Research Projects Using Text Mining and Link Analysis , 2003 .

[11]  Dunja Mladenic,et al.  Data Mining and Decision Support , 2003 .

[12]  Marko Grobelnik,et al.  User Profiling for Interest-focused Browsing History , 2005 .

[13]  Dunja Mladenic,et al.  Text and Web Mining , 2003 .

[14]  Ian Witten,et al.  Data Mining , 2000 .

[15]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[16]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[17]  Dunja Mladenic,et al.  Web Mining: From Web to Semantic Web , 2004, Lecture Notes in Computer Science.

[18]  Steffen Staab,et al.  Discovering Conceptual Relations from Text , 2000, ECAI.

[19]  Gilles Bisson,et al.  Designing Clustering Methods for Ontology Building - The Mo'K Workbench , 2000, ECAI Workshop on Ontology Learning.

[20]  Dunja Mladenic,et al.  Visualization of News Articles , 2004, Informatica.

[21]  Dunja Mladenic,et al.  Mapping Documents onto Web Page Ontology , 2003, EWMF.

[22]  George Karypis,et al.  A Comparison of Document Clustering Techniques , 2000 .