Text Mining and Document Management

Controlling and managing the flood of data

Under the generic term text mining, many different technologies used to index (unstructured) content are grouped. On the one hand, these technologies comprise of term extraction and aggregation as a basis for semantic indexing, retrieval and clustering solutions. On the other hand, categorization of documents, generation of abstracts to the point of detecting patterns and relationships between terms through steps of text analysis are the main aspects. These results can be presented in a “document warehouse” with methods from the Semantic Web environment and displayed with visualization tools.

Workshop focusBasics of text mining for CI analysts

* "Information overload" problem
* Text mining: Substantial challenges
* Text mining functions: Text categorization, wrapper applications, text summary, language identification, topic clustering, information extraction, text analy­sis
* Text mining and Competitive Intelligence

IT support for text mining

* Information freedom law
* Software tools to improve the efficiency of re­search
* Displaying analysis methods
* Cost-benefit optimization, aspects of adding value
* Information flow diagrams
* Filing system
* Reporting of data, information and facts
* Improving the impact of researched results

Implementation of text mining systems

* Case study "Implementation of a text mining system"

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