Case studies: Commercial domain, single mining tasks systems: document explorer

Authors:
Ronen Feldman
Affiliations:
Director, Data Mining Laboratory, Department of Mathematics and Computer Science, Bar-Ilan University, Ramat-Gan, Israel
Venue:
Handbook of data mining and knowledge discovery
Year:
2002

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Abstract

Document Explorer is a data mining system for document collections. Such a collection represents an application domain, and the primary goal of the system is to derive patterns that provide knowledge about this domain. Additionally, the derived patterns can be used to browse the collection. Document Explorer searches for patterns that capture relations between concepts of the domain. The patterns that have been verified as interesting are structured and presented in a visual user interface allowing the user to operate on the results to refine and redirect mining queries or to access the associated documents. The system offers preprocessing tools to construct or refine a knowledge base of domain concepts and to create an intermediate representation of the document collection that will be used by all subsequent data mining operations. The main pattern types the system can search for are frequent sets, associations (see Chapter 16.2.3 of this handbook), concept distributions, and keyword graphs.