Advertisement

Context Queries and Enhanced Reports

  • Witold Abramowicz
  • Paweł Kalczyński
  • Krzysztof Węcel

Abstract

This chapter concludes the considerations conducted in previous chapters. The final goal of the eDW system, i.e. enhanced Data Warehouse Report, is reached.

Keywords

Time Constraint Data Warehouse Query Expansion Time Histogram Cosine Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abramowicz W, Kalczytiski PJ, Wçcel K (200 lb) Time Consistency among Structured and Unstructured Contents in the Data Warehouse. In: Mehdi Khosrowpour (ed) Managing Information Technology in a Global Economy, Proc of IRMA 2001, Toronto. Idea Group Publishing, Hershey London Melbourne Singapore, pp 815-818Google Scholar
  2. Baeza-Yates R, Ribeiro-Neto B (1999) Modern Information Retrieval. Addison-Wesley ACM Press New York, USAGoogle Scholar
  3. Belkin NJ, Cool C, Head J, Jeng J, Kelly D, Lin S et al. (1999) Relevance Feedback versus Local Context Analysis as Term Suggestion Devices: Rutgers' TREC-8 Interactive Track Experience. Proc of the 8th Text Retrieval Conference (TREC-8). NIST Special PublicationGoogle Scholar
  4. Bettini C, Jajodia S, Wang SX (2000) Time Granularities in Databases, Data Mining, and Temporal Reasoning. Springer Verlag, Berlin HeidelbergzbMATHGoogle Scholar
  5. Crouch CJ, Yang B (1992) Experiments in automatic statistical thesaurus construction. In: Proc of the ACM SIGIR Conference on Research and Development in Information Retrieval, Copenhagen, Denmark, pp 77-88Google Scholar
  6. Foskett DJ (1997) Thesaurus. In: Sparck-Jones K, Willet P (eds) Readings in Information Retrieval. Morgan Kaufmann Publishers, pp 111-134Google Scholar
  7. Kalczyñski P (2001) Software Agents to Filter Business Information from the Internet to the Data Warehouse. Doctoral Dissertation, Department of Computer Science, Faculty of Economics, The Poznaií University of Economics, Poznarí, PolandGoogle Scholar
  8. O’Day VL, Jeffries R (1993) Orienteering in an information landscape: how information seekers get from here to there. In: Proc of the 1NTERCHI’93, Amsterdam, Netherlands. IOS Press, AprilGoogle Scholar
  9. Qiu Y, Frei HP (1993) Concept based query expansion. In: Proc of the 16th ACM SIGIR Conference on Research and Development in Information Retrieval, Pittsburgh, PA, pp 160-169CrossRefGoogle Scholar
  10. Reynolds H (2000) Avoiding Information Overload. DB2 Magazine, Summer 2000. http://www.db2mag.com/db_area/archives/2000/q2/reynolds.shtml
  11. Roen W (2000) Using Enterprise Information Portals to Tackle Information Gridlock. Database Trends, December. http://www.databasetrends.com/00.december/12.f.e.usingenterprise.html
  12. Salton G, McGill M (1983) Introduction to Modern Information Retrieval. McGraw-Hill Book Company, USAzbMATHGoogle Scholar
  13. Wgcel K (2001) Profilowanie hurtowni danych dla potrzeb filtrowania informacji ekonomicznej (Profiling the Data Warehouse for Business Information Filtering). Doctoral Dissertation, Department of Computer Science, Faculty of Economics, The Poznaú University of Economics, Poznaií, Poland (in Polish)Google Scholar
  14. Xu J (1997) Solving the Word Mismatch Problem Through Automatic Text Analysis. Doctoral Dissertation, University of Massachusetts, AmherstGoogle Scholar
  15. Xu J, Croft WB (1996) Query Expansion Using Local and Global Document Analysis. In: Proc of the 19th International Conference on Research and Development in Information Retrieval (SIGIR 96), Zurich, Switzerland, pp 4-11Google Scholar

Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • Witold Abramowicz
    • 1
  • Paweł Kalczyński
    • 1
  • Krzysztof Węcel
    • 1
  1. 1.Department of Computer ScienceThe Poznań University of EconomicsPoznańPoland

Personalised recommendations