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Research Goal

To make good decisions, businesses try to gather good intelligence information.  Yet managing large quantities of unstructured information and data stand in the way of greater business knowledge.  Effective tools for increasing business intelligence used to access relevant content, in different formats must include analysis tools for searching, browsing, and summarization.  Useful business intelligence content needs to be credible, timely, and relevant.  We created eBizPort to facilitate the process of acquiring business intelligence in the Information Technology industry.  The eBizPort contains content from the leading news and commentary providers in the IT domain, which was collected using a new vertical collection-building technique.  We have integrated a number of post-retrieval tools to support browsing and investigate techniques to overcome information overload.

 

Acknowledgements

We would like to express our gratitude to NSF Digital Library Initiative-2, "High-performance Digital Library Systems:  From Information Retrieval to Knowledge Management,"  IIS-9817473, April 1999-March 2002

Approach & Methodology

Content (over 400,00 URLs) from the following providers: Computerworld The Industry Standard Wired PCWorld InternetWeek InfoWorld C|Net IDG ITWord CIO Business 2.0 Informationweek RedHerring Techniques: Meta-searching spider that gathers content from major news providers Java parsing and indexing programs to create importable database files Kohonen Self-Organization Map (SOM): Algorithms-single and multi-layer self-organizing maps for information categorization and visualization. Database stored procedures to import and manage inverted index and provide searching functionality SOM display Folder Clustering of main document topics AZ Noun Phraser for topic extraction

Team Members

Dr. Hsinchun Chen hchen@eller.arizona.edu    Byron Marshall byronm@eller.arizona.edu    Daniel McDonald dmm@eller.arizona.edu    Wingyan Chung wchung@bpa.arizona.edu

Publications

Byron Marshall, Dan McDonald, Hsinchun Chen, Wingyan Chung “EBizPort: Collecting and Analyzing Business Intelligence Information” Journal of the American Society for Information Science and Technology (JASIST) Special Issue on Document Search Interface Design for Large-scale Collections and Intelligent Access, (accepted for publication 2003, forthcoming 2004)

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