An Improved Performance of Keyword Search Using Graph Structured Knowledge

Authors(3) :-C. Shanker, T. Usha, D. Chitty

Keyword search is associate degree intuitive paradigm for looking joined knowledge sources on the online. We have a tendency to propose to route keywords solely to relevant sources to cut back the high value of process keyword search queries over all sources. We have a tendency to propose a unique methodology for computing top-k routing plans supported their potentials to contain results for a given keyword question. We have a tendency to use a keyword-element relationship outline that succinctly represents relationships between keywords and therefore the knowledge parts mentioning them. A structure evaluation mechanism is projected for computing the relevancy of routing plans supported scores at the amount of keywords, knowledge parts, component sets, and sub graphs that connect these parts. Experiments administrated mistreatment a hundred and fifty publically accessible sources on the online showed that valid plans (precision@1 of zero.92) that square measure extremely relevant (mean reciprocal rank of zero.89) are often computed in one second on the average on one laptop. Further, we have a tendency to show routing greatly helps to enhance the performance of keyword search, while not compromising its result quality.

Authors and Affiliations

C. Shanker
Associate Professor, Department of Computer Science & Engineering in Sri Indu College of Engineering & Technology, Hyderabad, India
T. Usha
pursuing M.Tech (Computer Science) Sri Indu College of Engineering & Technology, Affiliated to JNTU-Hyderabad, India
D. Chitty
pursuing M.Tech (Computer Science & Engineering), Sri Indu College of Engineering & Technology, Affiliated to JNTU-Hyderabad, India

Keyword search, keyword question, keyword question routing, graph-structured knowledge, RDF

  1. G. Li, S. Ji, C. Li, and J. Feng, "Efficient Type-Ahead Search on Relational Data: A Tastier Approach," Proc. ACM SIGMOD Conf.,pp. 695-706, 2009.
  2. V. Kacholia, S. Pandit, S. Chakrabarti, S. Sudarshan, R. Desai, and H. Karambelkar, "Bidirectional Expansion for Keyword Search on Graph Databases," Proc. 31st Int’l Conf. Very Large Data Bases (VLDB),pp. 505-516, 2005.
  3. H. He, H. Wang, J. Yang, and P.S. Yu, "Blinks: Ranked Keyword Searches on Graphs,” Proc. ACM SIGMOD Conf.,pp. 305-316,2007.
  4. G. Li, B.C. Ooi, J. Feng, J. Wang, and L. Zhou, "Ease: An Effective 3-in-1 Keyword Search Method for Unstructured, Semi-Structured and Structured Data," Proc. ACM SIGMOD Conf.,pp. 903-914,2008.
  5. T. Tran, H. Wang, and P. Haase, "Hermes: Data Web Search on a Pay-as-You-Go Integration Infrastructure," J. Web Semantics,vol. 7,no. 3, pp. 189-203, 2009.
  6. R. Goldman and J. Widom, "DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases,” Proc. 23rd Int’l Conf. Very Large Data Bases (VLDB),pp. 436-445,1997.
  7. G. Ladwig and T. Tran, "Index Structures and Top-K Join Algorithms for Native Keyword Search Databases," Proc. 20th ACM Int’l Conf. Information and Knowledge Management (CIKM),pp. 1505-1514, 2011.
  8. B. Yu, G. Li, K.R. Sollins, and A.K.H. Tung, "Effective KeywordBased Selection of Relational Databases," Proc. ACM SIGMOD Conf.,pp. 139-150, 2007.
  9. Q.H. Vu, B.C. Ooi, D. Papadias, and A.K.H. Tung, "A Graph Method for Keyword-Based Selection of the Top-K Databases,” Proc. ACM SIGMOD Conf.,pp. 915-926, 2008.
  10. V. Hristidis and Y. Papakonstantinou, "Discover: Keyword Search in Relational Databases," Proc. 28th Int’l Conf. Very Large Data Bases (VLDB),pp. 670-681, 2002.
  11. L. Qin, J.X. Yu, and L. Chang, "Keyword Search in Databases: The Power of RDBMS," Proc. ACM SIGMOD Conf.,pp. 681-694, 2009.

Publication Details

Published in : Volume 1 | Issue 5 | September-October 2015
Date of Publication : 2015-10-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 106-109
Manuscript Number : IJSRSET1522153
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

C. Shanker, T. Usha, D. Chitty, " An Improved Performance of Keyword Search Using Graph Structured Knowledge, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 5, pp.106-109, September-October-2015.
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