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BusSEngine: a business search engine

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Abstract

With the emergence of World Wide Web, business’ databases are increasingly being queried directly by customers. The customers may not be aware of the underlying data and its structure, and might have never learned a query language that enables them to issue structured queries. Some of the business’ employees who query the databases may also not be aware of the structure of the data, but they are likely to be aware of some labels of elements containing data. We propose in this article: (1) an XML Keyword-Based search engine for answering business’ customers called BusSEngine-K, and (2) an XML loosely Structured-Based search engine for answering business’ employees called BusSEngine-L. The two engines employ novel context-driven search techniques and are built on top of XQuery search engine. The two engines were evaluated experimentally and compared with three recently proposed XML search engines. The results showed marked improvement.

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References

  1. Amer-Yahia S, Cartmola E, Deutsch A (2006) Flexible and efficient XML search with complex. Full-text predicates. ACM SIGMOD, Chicago

    Google Scholar 

  2. Agrawal S, Chaudhuri S, Das G (2002) DBXplorer: a system for keyword-based search over relational databases. ICDE, San Jose

    Google Scholar 

  3. Aditya B, Bhalotia G, Sudarshan S (2002) BANKS: browsing and keyword searching in relational databases. VLDB, Hong Kong

    Google Scholar 

  4. Balmin A, Hristidis V, Papakonstantinon Y, Koudas N (2003) A system for keyword proximity search on XML databases. VLDB, Berlin

    Google Scholar 

  5. Balmin A, Hristidis V, Papakonstantinon Y (2003) Keyword proximity search on XML graphs. ICDE, Bangalore

    Google Scholar 

  6. Balmin A, Hristidis V, Papakonstantinon Y (2004) ObjectRank: authority-based keyword search in databases. VLDB, Toronto

    Google Scholar 

  7. Botev C, Shao F, Guo L (2003) XRANK: ranked keyword search over XML documents. ACM SIGMOD, San Diego

    Google Scholar 

  8. Barbosa D, Mendelzon A, Keenleyside J, Lyons K (2002) ToXgene: a template-based data generator for XML. WebDB, Madison, Wisconsin. http://www.cs.toronto.edu/tox/toxgene/downloads.html

  9. Cohen S, Mamou J, Sagiv Y (2003) XSEarch: a semantic search engine for XML. VLDB, Berlin

    Google Scholar 

  10. Cohen S, Kanza Y (2005) Interconnection semantics for keyword search in XML. ACM CIKM, Bremen

    Google Scholar 

  11. Chamberlin D, Fankhauser P, Florescu D, Robie J (2007) XML query use cases. W3C Working Draft 2007. http://www.w3.org/TR/xquery-use-cases/

  12. Denny M (2002) Ontology building: a survey of editing tools. O’Reilly XML.COM. http://www.xml.com/2002/11/06/Ontology_Editor_Survey.html

  13. Hristidis V, Papakonstantinou Y (2002) DISCOVER: keyword search in relational databases. VLDB, Hong Kong

    Google Scholar 

  14. INEX (2005) Initiative for the evaluation of XML retrieval (INEX), 2005. http://inex.is.informatik.uni-duisburg.de/2005/

  15. Jagadish HV, Patel JM (2006) TIMBER. University of Michigan. http://www.eecs.umich.edu/db/timber/

  16. Knublauch H, Musen M, Rector A (2002) Editing description logic ontologies with the Protégé OWL Plugin. Technical discussion for logicians, Stanford University

  17. Katz H (2005) XQEngine version 0.69. Fatdog Software. http://www.fatdog.com/. The engine downloaded from: http://sourceforge.net/projects/xqengine

  18. Li Y, Yu C, Jagadish H (2004) Schema-free XQuery. The 30th international conference on Very Large Data Bases (VLDB) conference, Toronto, Canada

  19. Leung H, Chung F, Chan C (2004) On the use of hierarchical information in sequential mining-based XML document similarity computation. Knowl Inf Syst 7(4): 476–498

    Article  Google Scholar 

  20. Nayak R (2008) Fast and effective clustering of XML data using structural information. Knowl Inf Syst 14(2): 197–215

    Article  MathSciNet  Google Scholar 

  21. Rijsbergen V (1979) Information retrieval. Butterworth-Heinemann, London

    Google Scholar 

  22. Schmidt AR, Waas F, Kersten ML, Florescu D, Manolescu I, Carey MJ, Busse R (2002) The XML benchmark project. Technical Report INS-R0103, CWI. http://www.xml-benchmark.org/. Downloaded from: http://monetdb.cwi.nl/xml/downloads.html

  23. Taha K, Elmasri R (2007) OOXSearch: a search engine for answering loosely structured xml queries using OO programming. In: The 24th British national conference on databases (BNCOD), Glasgow, Scotland

  24. Xu X, Papakonstantinou Y (2005) Efficient keyword search for smallest LCAs in XML databases. SIGMOD International Conference on Management of Data, Baltimore

    Google Scholar 

  25. Yang J, Cheung W, Chen X (2008) Learning element similarity matrix for semi-structured document analysis. Knowl Inf Syst 19(1): 50–76

    Google Scholar 

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Correspondence to Kamal Taha.

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Taha, K., Elmasri, R. BusSEngine: a business search engine. Knowl Inf Syst 23, 153–197 (2010). https://doi.org/10.1007/s10115-009-0210-6

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  • DOI: https://doi.org/10.1007/s10115-009-0210-6

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