Machine learning from text and text mining cover a wide range of topics both in terms of methods and applications, some of which are listed here as examples:
Scholz/Klinkenberg/2006b |
Scholz, Martin and Klinkenberg, Ralf.
Boosting Classifiers for Drifting Concepts.
In
Intelligent Data Analysis (IDA), Special Issue on Knowledge Discovery from Data Streams,
Vol. 11,
No. 1,
pages 3--28,
2007.
|
Deutsch/2006a |
Deutsch, Stephan.
Outlier Detection in USENET Newsgruppen.
University of Dortmund,
2006.
|
Hennig/Wurst/2006a |
Hennig, Sascha and Wurst, Michael.
Incremental Clustering of Newsgroup Articles.
In
Moonis Ali and Richard Dapoigny (editors),
Proceedings of the International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 06),
pages 332--341,
Berlin, Heidelberg,
Springer,
2006.
|
Mierswa/etal/2006a |
Mierswa, Ingo and Wurst, Michael and Klinkenberg, Ralf and Scholz, Martin and Euler, Timm.
YALE: Rapid Prototyping for Complex Data Mining Tasks.
In
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2006),
pages 935--940,
ACM,
New York, USA,
ACM Press,
2006.
|
Scholz/Klinkenberg/2006a |
Scholz, Martin and Klinkenberg, Ralf.
Boosting Classifiers for Drifting Concepts.
No. 6/06,
Collaborative Research Center on the Reduction of Complexity for Multivariate Data Structures (SFB 475), University of Dortmund,
Dortmund, Germany,
2006.
|
Klinkenberg/2005a |
Klinkenberg, Ralf.
Meta-Learning, Model Selection, and Example Selection in Machine Learning Domains with Concept Drift.
In
Furnkranz, Johannes and Grieser, Gunter (editors),
Annual workshop of the special interest group on machine learning, knowledge discovery, and data mining (FGML-2005) of the German Computer Science Society (GI) within the workshop week \em Learning -- Knowledge Discovery -- Adaptivity (LWA-2005),
Saarbrucken, Germany,
2005.
|
Roessler/Morik/2005a |
Roessler, Marc and Morik, Katharina.
Using Unlabeled Texts for Named-Entity Recognition.
In
Tobias Scheffer and Stefan Rüping (editors),
ICML Workshop on Multiple View Learning,
2005.
|
Scholz/Klinkenberg/2005a |
Scholz, Martin and Klinkenberg, Ralf.
An Ensemble Classifier for Drifting Concepts.
In
Gama, J. and Aguilar-Ruiz, J. S. (editors),
Proceedings of the Second International Workshop on Knowledge Discovery in Data Streams,
pages 53--64,
Porto, Portugal,
2005.
|
Klinkenberg/2004a |
Klinkenberg, Ralf.
Learning Drifting Concepts: Example Selection vs. Example Weighting.
In
Intelligent Data Analysis (IDA), Special Issue on Incremental Learning Systems Capable of Dealing with Concept Drift,
Vol. 8,
No. 3,
pages 281--300,
2004.
|
Klinkenberg/Rueping/2003a |
Klinkenberg, Ralf and Rüping, Stefan.
Concept Drift and the Importance of Examples.
In
Franke, Jurgen and Nakhaeizadeh, Gholamreza and Renz, Ingrid (editors),
Text Mining -- Theoretical Aspects and Applications,
pages 55--77,
Berlin, Germany,
Physica-Verlag,
2003.
|
Daniel/etal/2002a |
Daniel, Guido and Dienstuhl, J. and Engell, S. and Felske, S. and Goser, K. and Klinkenberg, R. and Morik, K. and Ritthoff, O. and Schmidt-Traub, H..
Novel Learning Tasks, Optimization, and Their Application.
In
Schwefel, H.-P. and Wegener, I. and Weinert, K. (editors),
Advances in Computational Intelligence -- Theory and Practice,
pages 245--318,
Berlin, Germany,
Springer,
2002.
|
Euler/2002a |
Timm Euler.
Tailoring Text Using Topic Words: Selection and Compression.
In
Proceedings of the 13th International Workshop on Database and Expert Systems Applications (DEXA),
pages 215--219,
Los Alamitos, CA,
IEEE Computer Society Press,
2002.
|
Joachims/2002b |
Joachims, Thorsten.
Learning to Classify Text using Support Vector Machines.
Vol. 668,
Kluwer,
2002.
|
Klinkenberg/2002a |
Klinkenberg, Ralf.
Transductive Learning of Drifting Concepts.
No. CI-125/02,
Collaborative Research Center 531, University of Dortmund,
Dortmund, Germany,
2002.
|
Klinkenberg/etal/2002a |
Klinkenberg, Ralf and Ritthoff, Oliver and Morik, Katharina.
Novel Learning Tasks From Practical Applications.
In
Henze, Nicola and Kókai, Gabriella and Zeidler, Jens (editors),
LLA'02: Lehren -- Lernen -- Adaptivitat, Proceedings of the workshop of the special interest groups Machine Learning (FGML), Intelligent Tutoring Systems (ILLS), and Adaptivity and User Modeling in Interactive Systems (ABIS) of the German Computer Science Society (GI),
pages 46--59,
Hannover, Germany,
University of Hannover,
2002.
|
Joachims/2001a |
Thorsten Joachims.
The Maximum-Margin Approach to Learning Text Classifiers: Methods, Theory, and Algorithms.
Fachbereich Informatik, Universität Dortmund,
2001.
|
Klinkenberg/2001a |
Klinkenberg, Ralf.
Using Labeled and Unlabeled Data to Learn Drifting Concepts.
In
Kubat, Miroslav and Morik, Katharina (editors),
Workshop notes of the IJCAI-01 Workshop on \em Learning from Temporal and Spatial Data,
pages 16--24,
IJCAI,
Menlo Park, CA, USA,
AAAI Press,
2001.
|
Klinkenberg/Joachims/2000a |
Klinkenberg, Ralf and Joachims, Thorsten.
Detecting Concept Drift with Support Vector Machines.
In
Langley, Pat (editors),
Proceedings of the Seventeenth International Conference on Machine Learning (ICML),
pages 487--494,
San Francisco, CA, USA,
Morgan Kaufmann,
2000.
|
Joachims/99c |
Thorsten Joachims.
Transductive Inference for Text Classification using Support Vector Machines.
In
Proceedings of the 16th Int. Conf. on Machine Learning (ICML),
pages 200--209,
San Francisco, CA,
Morgan Kaufmann Publishers Inc.,
1999.
|
Klinkenberg/99a |
Klinkenberg, Ralf.
Learning Drifting Concepts with Partial User Feedback.
In
Perner, Petra and Fink, Volkmar (editors),
Beitrage zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen (FGML-99),
Magdeburg, Germany,
1999.
|
Armstrong/etal/98a |
Armstrong, Robert and Freitag, Dayne and Joachims, Thorsten and Mitchell, Tom.
WebWatcher: A Learning Apprentice for the World Wide Web.
In
R. Michalski and I. Bratko and M. Kubat (editors),
Machine Learning and Data Mining,
pages 297-312,
Wiley,
1998.
|
Hoelscher/98a |
Holscher, Markus.
Informationsextraktion aus Freitext-Eintragen einer Datenbank.
Fachbereich Informatik, Universitat Dortmund,
1998.
|
Joachims/98a |
Joachims, Thorsten.
Text Categorization with Support Vector Machines: Learning with Many Relevant Features.
In
Claire N\'edellec and C\'eline Rouveirol (editors),
Proceedings of the European Conference on Machine Learning,
pages 137 -- 142,
Berlin,
Springer,
1998.
|
Joachims/Mladenic/98a |
T. Joachims and D. Mladeni\`c.
Browsing-Assistenten, Tour Guides und adaptive WWW-Server.
In
Kunstliche Intelligenz,
Vol. 3,
No. 28,
pages 23 -- 29,
1998.
|
Klinkenberg/98a |
Klinkenberg, Ralf.
Maschinelle Lernverfahren zum adaptiven Informationsfiltern bei sich verandernden Konzepten.
Fachbereich Informatik, Universitat Dortmund, Germany,
1998.
|
Klinkenberg/Renz/98a |
Klinkenberg, Ralf and Renz, Ingrid.
Adaptive Information Filtering: Learning in the Presence of Concept Drifts.
In
Sahami, Mehran and Craven, Mark and Joachims, Thorsten and McCallum, Andrew (editors),
Workshop Notes of the ICML/AAAI-98 Workshop \em Learning for Text Categorization,
pages 33--40,
Menlo Park, CA, USA,
AAAI Press,
1998.
|
Klinkenberg/Renz/98b |
Klinkenberg, Ralf and Renz, Ingrid.
Adaptive Information Filtering: Learning Drifting Concepts.
In
Wysotzki, F. and Geibel, P. and Schadler, K. (editors),
Beitrage zum Treffen der GI-Fachgruppe 1.1.3 Maschinelles Lernen (FGML-98),
No. 98/11,
pages 98--105,
Germany,
Fachbereich Informatik, TU Berlin,
1998.
|
Joachims/97a |
Joachims, Thorsten.
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization.
In
Proceedings of International Conference on Machine Learning (ICML),
1997.
|
Joachims/97b |
T. Joachims.
Text Categorization with Support Vector Machines: Learning with Many Relevant Features.
No. 23,
Universitat Dortmund, LS VIII-Report,
1997.
|
Joachims/97c |
Joachims, Thorsten.
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization.
In
Proceedings of the 14th International Conference on Machine Learning ICML97,
pages 143--151,
1997.
|
Schewe/97b |
Schewe, Sandra.
Automatische Kategorisierung von Volltexten unter Anwendung von NLP-Techniken.
Fachbereich Informatik, Universitat Dortmund,
1997.
|
Boyan/etal/96a |
Boyan, J. and Freitag, D. and Joachims, T..
A Machine Learning Architecture for Optimizing Web Search Engines.
In
AAAI Workshop on Internet Based Information Systems,
1996.
|
Joachims/96a |
Joachims, Thorsten.
Einsatz eines intelligenten, lernenden Agenten fur das World Wide Web.
Fachbereich Informatik, Universitat Dortmund,
1996.
|
Armstrong/etal/95a |
Armstrong, Robert and Freitag, Dayne and Joachims, Thorsten and Mitchell, Tom.
WebWatcher: A Learning Apprentice for the World Wide Web.
In
Proceedings of the 1995 AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments,
Stanford,
1995.
|
Joachims/etal/95a |
Joachims, Thorsten and Mitchell, Tom and Freitag, Dayne and Armstrong, Robert.
WebWatcher: Machine Learning and Hypertext.
In
Beitrage zum 7. Fachgruppentreffen MASCHINELLES LERNEN der GI-Fachgruppe 1.1.3,
pages 145 -- 149,
1995.
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