A Tree Based Association Rule Approach for XML Data with Semantic Integration
The use of eXtensible Markup Language (XML) in web, business and scientific databases lead to the development of methods, techniques and systems to manage and analyze XML data. Semi-structured documents suffer due to its heterogeneity and dimensionality. XML structure and content mining represent convergence for research in semi-structured data and text mining. As the information available on the internet grows drastically, extracting knowledge from XML documents becomes a harder task. Certainly, documents are often so large that the data set returned as answer to a query may also be very big to convey the required information. To improve the query answering, a Semantic Tree Based Association Rule (STAR) mining method is proposed. This method provides intentional information by considering the structure, content and the semantics of the content. The method is applied on Reuter’s dataset and the results show that the proposed method outperforms well.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1337980Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1944
 Markus Tresch, Neal Palmer and Allen Luniewski (1995), “Type Classification of Semi Structured documents”, In the proceedings of the 21st International Conference on Very Large Data Bases,pp.263-274.
 Jeonghee Yi and Neel Sundaresan, (2001), “A Classifier for semi structured documents”, In the Proceedings of 6th Internatnal Conference on Knowledge Discovery and Data Mining,pp.34-344
 Shashirekha H.L., Vanishree K.S., and Sumangala N,(2011),“Content and Structure Based Classification of Xml Documents”, International Journal Of Machine Intelligence , Vol. 3, No. 4, pp.376-380.
 Sekhar, G. S., and Krishna, S. M. , (2012), “Efficient Data Mining for XML Queries–Answering Support”, In the IOSR Journal of Computer Engineering, Vol.4, No.6, pp. 13-22.
 F. Llopis A. Ferrandez , J. L. Vicedo and A. Gelbukh,(2002), “Text segmentation for efficient information retrieval”, In the Proceedings of 3rd International Conference on Text Processing and Computational Linguistics,LNCS 2276: pp 373-380.
 Chen L, Bhowmick, SS, & Chia LT, (2004), “Mining association rules from structural deltas of historical XML documents”, In the Proceedings of Pacific-Asia conference on knowledge discovery and data mining, pp. 452-457.
 AliMohammadzadeh R, Soltan S & Rahgozar M, (2006), ‘Template guided association rule mining from XML documents’, Proceedings of 15th International World Wide Web Conference, pp. 963-964
 Tekli J, Chbeir R, & Yetongnon K (2007), “Structural similarity evaluation between XML documents and DTDs”, Proceedings of the 8th International Conference on Web Information Systems Engineering Nancy, pp. 196-211.
 Qiu W (2009), “Research and application of XML documents query based on weight cost”, Asia-Pacific Conference on information processing, vol.1, pp.525-528.
 Mazuran, M, Quintarelli, E, & Tanca, L 2012, ‘Data mining for XML query-answering support’, IEEE Transaction on Knowledge and Data Engineering, vol. 24, no. 8, pp. 1393-1407.
 Sekhar, G. S., and Krishna, S. M., (2012), “Efficient Data Mining for XML Queries–Answering Support”,In the IOSR Journal of Computer Engineering, Vol.4, No.6, pp. 13-22.
 Vikhe, P. B., & Gunjal, B. L. (2013), “Extracting Tree Based Association Rules from XML Document”, International Journal of Emerging Technology and Advanced Engineering,Vol. 3, No.6.
 Chiranjeevi, K., Vasantha, K., & Rao, C. M. (2013),“A Succinct Answering Prototype for XML Data”, In the international journal of Advanced and Innovative Research,Vol.2,No.11, pp. 642-651.
 Jacques Savoy,(1999) “A Stemming Procedure and Stop word List for General French Corpora”, In the Journal of the American Society for Information Science, Vol.50, No.10, pp 944-952.
 G. Salton, (1989), “Automatic text processing: the transformation, analysis, and retrieval of information by computer”. Addison-Wesley Longman Publishing Co. Boston, MA, USA 1989.
 Vurukonda, N., Reddy, G. R., C., Mounika, B., Yogyatha, G., Srujana, N., & Priya, P. K. (2013). “A Survey on Tree based Association Rules (TARs) from XML Documents”, In the International Journal of Research and computational Technology,Vol.5, No.1.