Prototype for Enhancing Search Engine Performance Using Semantic Data Search

Authors(2) :-Divya. J, C. Senthil Kumar

Information’s on Internet are vast that are retrieved by the search engines based on page ranks. But the search results are not related to one particular user’s environment. Many researches had been possessed to provide better results.  In this project, we propose a new system called as Semantic Search log Social Personalized Search which would be able to provide results for search query that relates to a particular user’s environment based on the users area of interests, his likes and dislikes etc.., Social networks are such domain in which we could obtain the user oriented information, which can be used for providing personalized search results. Here a supervised learning technique is used to learn about the user, based upon his interactions inside the system. This process can be able to make applicable for each and every registered user in this application. This can be done by proving the user basic information in their profile and get benefits from their each and every search.

When the user gets register with the system, it creates an ontological profile, when the user gets login into the social network and interacts with it the system updates the user ontological profile based upon their interaction. The search provision can be finding out in their home page after they get login. When the user searches a keyword using the search engine inside the social network, it refers to the ontological profile of the user and displays the Personalized Search results. The system should be able to intelligently identify whether a search result has been useful to him or not and save it for his future reference when he searches for the same or similar keyword next time. The main objective of this project involves with search engine and its optimization methods. A new technique called as ontology search logs is introduced, which will be used for customized search logs according to the user’s define input based on  his/her area of interests, his/her likes and dislikes,. This application will be processed in any type of the search engine. 

Authors and Affiliations

Divya. J
Department of Information Technology, SNS College of Technology, Coimbatore, Tamil Nadu, India
C. Senthil Kumar
Department of Information Technology, SNS College of Technology, Coimbatore, Tamil Nadu, India

Search Engine, Ontology technique, Semantic Search, Google search, web crawler.

  1. Brusilovsky, P.: Adaptive Hypermedia. User Model. UserAdapt. Interact., Vol. 11, 2001, No. 1–2, pp. 87–110.
  2.  Brusilovsky, P.—Kobsa, A.—Nejdl, W. Eds.: The Adaptive Web, Methods and Strategies of Web Personalization. LNCS 4321, Springer 2007.
  3. N. R. Shadbolt, W. Hall, and T. Berners-Lee, “The semantic web: Revisited,” IEEE-Intelligent Systems, vol. 21, issue 3, pp. 96–101, May 2006.
  4.  T. Burners-Lee, J. Hendler, and O. Lassila, “The semantic web,” Scientific American, vol. 284(5), May 2001
  5. E. Mäkelä. "Survey of semantic search research". In: Proceedings of the Seminar on Knowledge Management on the Semantic Web, Department of Computer Science, University of Helsinki (2005)
  6.  Ramprakash, S. K. Malik, N. Prakash, S. Rizvi , "A Comparative Study of Different Types of Search Engines in Context of Semantic Web”, National Conference on Advancements in Information & Communication Technology (NCAICT) , on March 15-16, 2008.
  7. W.A. PINHEIRO, A. Maria , C. Moura. "Semantic Search in Portals using Ontologies". I Workshop de Web Semântica (WWS2004), Brasília, 22 de outubro de 2004.
  8. C.Patel, K.Supekar, YLee, and E.Park, ”Ontokhoj: A semantic web portal for ontology searching ,ranking and classification ,”in Proc.of ACM 5th International Workshop on Web Information and Data Management (WIDM),New Orleans, pp.58-61,2003.
  9. E. Thomas, J. Z. Pan, D. H. Sleeman. "ONTOSEARCH2: Searching Ontologies Semantically". In Proc. of OWL Experiences and Directions Workshop, 2007.
  10. H. Alani, N. Noy, N. Shah, N. Shadbolt, M. Musen "Searching Ontologies Based on Content: Experiments in the Biomedical Domain In: 4th International Conference on Knowledge Capture.ACM Press; p.55–62, 2007.
  11. D. Taibi, M. Gentile, L. Seta. "A semantic search engine for learning resources". Third International Conference on Multimedia and Information & Communication Technologies in Education.2005.
  12. Chirita, P. Nejdl, W. Paiu, R. and Kohlschutter, C. (2005) Using ODP Metadata to Personalize Search. Proc. SIGIR ’05, Salvador, Brazil, 15-19 August, pp. 178-185, ACM Press, New York, NY, USA.
  13. Jason J. Jung,” Semantic business process integration based on ontology alignment” Sciencedirect, Volume 36, Issue 8, October 2009, Pages 11013–11020.
  14. N.T. Nguyen, R. Kowalczyk and S.M. Chen,” BizKB: A Conceptual Framework for Dynamic Cross-Enterprise Collaboration”, Springer  ICCCI 2009,LNASI 5796,pp. 401-4012,2009.
  15. Pedrinaci, C. ; Knowledge Media Inst., Open Univ., Milton Keynes ; Domingue, J. ; Brelage, C. ; van Lessen, T.  “Semantic Business Process Management: Scaling Up the Management of Business Processes “,Semantic Computing, 2008 IEEE International Conference on Aug. 2008, pp:546 – 553

Publication Details

Published in : Volume 2 | Issue 1 | January-February 2016
Date of Publication : 2016-02-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 314-320
Manuscript Number : IJSRSET162159
Publisher : Technoscience Academy

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

Cite This Article :

Divya. J, C. Senthil Kumar, " Prototype for Enhancing Search Engine Performance Using Semantic Data Search, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 1, pp.314-320, January-February-2016.
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