Accelerating the Response of Query in Semantic Web

Автор: Nooshin Azimi, Shahla Kiani

Журнал: International Journal of Computer Network and Information Security(IJCNIS) @ijcnis

Статья в выпуске: 8 vol.6, 2014 года.

Бесплатный доступ

Today, XML has become one of the important formats of saving and exchanging data. XML structure flexibility enhances its use, and the content of XML documents is increasing constantly. As a result, since file management system is not able to manage such content of data, managing XML documents requires a comprehensive management system. With the striking growth of such databases, the necessity of accelerating the implementing operation of queries is felt. In this paper, we are searching for a method that has required ability for a large set of queries; the method that would access fewer nodes and would get the answer through a shorter period of time, compared to similar ways; the method which has the ability of matching with similar ways indicator, and can use them to accelerate the queries. We are seeking a method which is able to jump over the useless nodes and produces intermediate data, as compared to similar ones. A method by which nodes processing are not performed directly and automatically through a pattern matching guide.

Еще

Query, Semantic Web, Optimization, XML Structure

Короткий адрес: https://sciup.org/15011328

IDR: 15011328

Список литературы Accelerating the Response of Query in Semantic Web

  • Sayyed Kamyar Izadi, Mostafa S. Haghjoo, Theo H¨arder,” S3: Processing tree-pattern XML queries with all logical operators, Data & Knowledge Engineering “Volume 72, Pages 31-62. (2011), doi: 10.1016/j.datak.2011.09.003.
  • SangKeun Lee, Byung-Gul Ryu, Kun-Lung Wu, Examining the impact of data-access cost on XML twig pattern matching Original Research Article Information Sciences”. , Volume 203, Pages 24-43, October 2012.
  • Chung, C., Min, J., Shim, K. Apex:" An adaptive path index for xml data.", In Proc ACM Conference on Management of Data SIGMOD: 121 - 132(2005).
  • Cooper. B., Sample. N., Franklin. M., Hjaltason. G., Shadmon. M. A Fast Index for Semistructed Data, In Proc. 14th VLDB conference: 341 – 350(2008).
  • R. Kaushik, P. Shenoy, P. Bohannon, and E. Gudes."Exploiting Local Similarity for Indexing Paths in Graph-Structured Data". In IEEE/ICDE, pages 129--140, San Jose, California, 2009.
  • Kaushik. R., Bohannon. P., Naughton J. and Korth. H, Covering Indexes for Branching Path Queries, In Proc. 11rd SIGMOD Conference: 133 – 144(2010).
  • Kaushik. R., Krishnamurthy. R., Naughton. J., and Ramakrishna. R. On the integration of structure indexes and inverted lists, In Proc SIGMOD Conference: 779 - 790 (2009).
  • Fouad, K., Harb, H. & Nagdy, N. (2011). Semantic Web supporting Adaptive E-Learning to build and represent Learner Model. The Second International Conference of E-learning and Distance Education (eLi 2011) – Riyadh.
  • Milo T., and Suciu D.., Index Structures for Path Expressions. In Proc. 7th .ICDT: 277 - 295(2008).
  • Yiqun Chen,Jinyin Cao,” TakeXIR:a Type-Ahead Keyword Search Xml Information Retrieval System”,(IJEME) International Journal of Intelligent Systems and Applications ,Vol. 2, No. 8, August 2012.
  • Dewey. M. Dewey Decimal Classification System. http://www.mtsu.edu/~vvesper/dewey.html.
  • O’Neil. P. E., Pal. S., Cseri. I., Schaller. G., Westbury. N., ORDPATHs: “Insert Friendly XML Node Labels.”, In Proc. SIGMOD Conference: 903-908 (2004).
  • Ley.Chael, DBLP Computer Science Bibliography, http://www.informatik.unitrier.de/ley/db/index.html (2011).
  • Vesin, B., Ivanovi, M., Kla?nja-Milicevic, A. & Budimac,Z. (2012). Protus 2. 0: Ontology-based semantic recommendation in programming tutoring system. Expert Systems with Applications 39 (2012) 12229–12246. Elsevier Ltd.
  • Nora Y. Ibrahim, Sahar A. Mokhtar, Hany M. Harb: “Towards an Ontology based integrated Framework for SemanticWeb.”, (IJCSIS) International Journal of Computer Science and Information Security(2010).
  • T. KRISHNA KISHORE, T.SASI VARDHAN, N. LAKSHMI NARAYANA:”Probabilistic Semantic Web Mining Using Artificial Neural Analysis “, (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 3, March (2010).
  • Nestorov S., Ullman J., Wiener J., and Chawathe S., Representative Objects :" Concise Representations of Semi structured, Hierarchical Data ",In Proc. ICDE: 79– 90(2010).
  • Goldman. R., Widom. J. Data Guides: "Enabling Query Formulation and Optimization in Semi structured Databases." ,In Proc. 23rd VLDB Conference: 436—445(2011).
  • Rizzolo. F. and Mendelzon. A., Indexing XML Data with ToXin, in Proc.5th. WebDB conference )2012).
Еще
Статья научная