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Survey on Information Retrieval in Semi Structured Data

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International Journal of Computer Applications
© 2011 by IJCA Journal
Number 1 - Article 1
Year of Publication: 2011
Authors:
Dayananda P
Dr. Rajashree Shettar
10.5120/3921-5524

Dayananda P and Dr. Rajashree Shettar. Article:Survey on Information Retrieval in Semi Structured Data. International Journal of Computer Applications 32(8):1-5, October 2011. Full text available. BibTeX

@article{key:article,
	author = {Dayananda P and Dr. Rajashree Shettar},
	title = {Article:Survey on Information Retrieval in Semi Structured Data},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {32},
	number = {8},
	pages = {1-5},
	month = {October},
	note = {Full text available}
}

Abstract

The rapid progress of network and storage technologies has led to a huge amount of electronic data such as webpages and XML data has been available on intra and internet. These electronic data are heterogeneous collection of ill-structured data that have no rigid structure, and are often called semi-structure data. These semi-structured data are stored in large repositories (XML databases) and stored as a graph internally in database with tuple as nodes and relationships as edges. As there is ever-growing availability of semi-structured information on web and digital libraries, there is a need of effective keyword search in order to fetch the correct and proximal result on Semi-Structured Data. This paper conducts a survey on how key word search can be performed on semi structure data, techniques involved in performing it, various result ranking strategies and result analysis techniques. It includes the analysis of various indexing schemes and different approaches for increase performance using caches for XML data in order to answer queries.

Reference

  • Liu, Z., Chen, Y.: Reasoning and identifying relevant matches for XML keyword search. PVLDB 1(1), 921–932 (2008).
  • Li, G., Feng, J., Wang, J., Zhou, L.: Effective keyword search for valuable LCAs over XML documents. In: CIKM, pp. 31–40 (2007).
  • Xu, Y., Papakonstantinou, Y.: Efficient keyword search for smallest LCAs in XML databases.In: SIGMOD Conference, pp. 537–538 (2005).
  • Li, Y., Yu, C., Jagadish, H.V.: Schema-free XQuery. In: VLDB, pp. 72–83 (2004).
  • Guo, L., Shao, F., Botev, C., Shanmugasundaram, J.: XRANK: ranked keyword search over XML documents. In: SIGMOD Conference, pp. 16–27 (2003).
  • Cohen, S., Mamou, J., Kanza, Y., Sagiv, Y.: XSEarch: a semantic search engine for XML.In: VLDB, pp. 45–56 (2003).
  • Sven Groppe, Jinghua Groppe, and Dirk Müller, “Result Merging Technique for Answering XPath Query over XSLT Transformed Data”,In: IEEE TRANSACTION(2009).
  • Cohen, S., Mamou, J., Kanza, Y., Sagiv, Y.: XSEarch: a semantic search engine for XML.In: VLDB, pp. 45–56 (2003).
  • Zheng, S., Zhou, A., Zhang, L., Lu, H.: DVQ: towards visual query processing of XML database systems. World Wide Web 6(2), 233–253 (2003).
  • Braga, D., Campi, A.: XQBE: a graphical environment to query XML data. World Wide Web 8(3), 287–316 (2005).
  • Ziyang Liu • Yi Chen , “Processing keyword search on XML: a survey”, Springer Science+Business Media, LLC 2011.
  • HaiDong,Farookh Khadeer Hussain, Elizabeth Chang,” A Survey in Traditional Information Retrieval Models”, IEEE 2008.
  • Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill (1983).
  • Li, J., Liu, C., Zhou, R.,Wang, W.: Suggestion of promising result types forXMLkeyword search. In: EDBT, pp. 561–572 (2010).
  • Huang, Y., Liu, Z., Chen, Y.: eXtract: a snippet generation system for XML search. PVLDB 1(2),1392–1395 (2008).
  • Huang, Y., Liu, Z., Chen, Y.: Query biased snippet generation in XML search. In: SIGMODConference, pp. 315–326 (2008).
  • Liu, Z., Huang, Y., Chen, Y.: Improving XML search by generating and utilizing informativeresult snippets. ACM Trans. Database Syst. 35(3), 19:1–19:45 (2010).
  • Liu, Z., Chen, Y.: Return specification inference and result clustering for keyword search onXML. ACM Trans. Database Syst. 35(2), 10:1–10:47 (2010).
  • Liu, Z., Huang, Y., Chen, Y.: Improving XML search by generating and utilizing informativeresult snippets. ACM Trans. Database Syst. 35(3), 19:1–19:45 (2010).
  • Yu, J.X., Luo, D., Meng, X., Lu, H.: Dynamically updating XML data: numbering schemerevisited. World WideWeb 8(1), 5–26 (2005).
  • Wu, X., Lee, M.-L., Hsu, W.: A prime number labeling scheme for dynamic ordered XML trees.In: ICDE, pp. 66–78 (2004).
  • Xu, L., Ling, T.W., Wu, H., Bao, Z.: DDE: from Dewey to a fully dynamic XML labeling scheme.In: SIGMOD Conference, pp. 719–730 (2009).
  • O’Neil, P.E., O’Neil, E.J., Pal, S., Cseri, I., Schaller, G., Westbury, N.: ORDPATHs: insertfriendlyXML node labels. In: SIGMOD Conference, pp. 903–908 (2004).
  • Schmidt, A., Kersten, M.L., Windhouwer, M.: Querying XML documents made easy: nearestconcept queries. In: ICDE, pp. 321–329 (2001).
  • Li, Y., Yu, C., Jagadish, H.V.: Schema-free XQuery. In: VLDB, pp. 72–83 (2004).
  • INEX. Initiative for the evaluation of xml retrieval. http://inex.is.informatik.uni-duisburg.de.
  • Golenberg, K., Kimelfeld, B., Sagiv, Y.: Supporting top-K keyword search in XML databasessearch in complex data graphs.In: SIGMOD Conference, pp. 927–940 (2008).
  • Chen, L.J., Papakonstantinou, Y.: Supporting top-K keyword search in XML databases. In:ICDE, pp. 689–700 (2010).
  • Liu, Z., Chen, Y.: Answering keyword queries on XML using materialized views. In: ICDE,pp. 1501–1503 (2008).
  • Schenkel, R., Theobald, M.: Structural feedback for keyword-based XML retrieval. In: ECIR,pp. 326–337 (2006).
  • S. Tata and G. M. Lohman. SQAK: doing more withkeywords. In SIGMOD, 2008.
  • I. De Felipe, V. Hristidis, and N. Rishe. Keywordsearch on spatial databases. In ICDE, 2008.