This is the ninth in the series of Text Mining workshops held in conjunction with SDM. Previous ones have taken place in 2001, 2002, 2003, 2006, 2007, 2008, and 2009, and at the most recent workshop (2010) in Columbus, OH, 39 authors representing industry, academia and national research laboratories from 4 different countries submitted a total of 14 papers. After careful review, 10 papers were selected for publication and presentation. In addition, SAS, Catalyst Repository Systems, Inc., and Small Bear Consulting, LLC sponsored the workshop and provided funds for student travel expenses.

General Topics

The proliferation of digital computing devices and their use in communication has resulted in an increased demand for systems and algorithms capable of mining textual data. Thus, the development of techniques for mining unstructured, semi-structured, and fully structured textual data has become quite important in both academia and industry. As a result, this Workshop tracks new developments in the field of Text Mining - the application of techniques of machine learning in conjunction with natural language processing, information extraction and algebraic/mathematical approaches to computational information retrieval. Issues addressed range from the development of new learning approaches to the parallelization of existing algorithms. The goal of this workshop is to provide a venue for researchers to share initial approaches and preliminary results of recent research in Text Mining. Through the careful selection and review of submitted workshop papers, we hope to provide a suitable selection of topics that will both generate interest and provide insight into the state of the field of Text Mining.

Special Topics - Text Mining with the Enron Data Set and VAST 2008/2009/2010 Contest Data

Because of the continued interest generated from the availability of the Enron data set of 1.3 million email messages (see Enron Email Dataset) and its versatility in terms of potential research topics (link analysis, pattern matching), researchers are encouraged to submit papers to this workshop. In addition, the text-based datasets of news events and scenario definition used in the IEEE Symposium on Visual Analytics Science and Technology (VAST) 2008 and 2009 Contests is an interesting corpus for research in topic detection/tracking, role playing, and scenario analysis (see VAST 2008 , VAST 2009 , and VAST 2010, contests for more details on those datasets).

Other Specific Topics of Interest Include:

Algorithms and Models

* Bayesian Models
* Concept Decomposition
* Orthogonal Decomposition
* Probabilistic Models
* Vector Space Models
* Latent Semantic Indexing
* Graph-based Models
* Text Streaming Models

Applications

* Clustering
* Factor Analysis
* Visualization Techniques
* Metadata Generation
* Information Extraction
* Text Classification
* Text Purification
* Text Segmentation
* Text Summarization
* Query Structures
* Trend Detection
* Distributed Storage and Retrieval