A Smart Searching Technique for Optimizing Relevant Web portal Discovery

Authors(4) :-S. Dhanasekaran, Vamshikrishna Bandari, Ravi Teja, Vishnu Gupta

This Research work is mainly deals about the Minimization of search options in a search engine. In general the keyword searched in any search engine gets some millions of results in microseconds. The output is obtained by analysing and processing a bulk data, thereby obtaining all relative or most searched sites and web pages. But here we put forth an idea for getting the fixed and efficient result in a short duration of time. The keyword searched in the search box gets the top 5 related sites per page through which the user can obtain the exact and efficient output. By this method of searching the search time for user and searching load for system and the server, both gets reduced which results in the effective usage of search engine.

Authors and Affiliations

S. Dhanasekaran
Department of CSE, Kalasalingam University, Srivilliputtur, Tamilnadu, India
Vamshikrishna Bandari
Department of CSE, Kalasalingam University, Srivilliputtur, Tamilnadu, India
Ravi Teja
Department of CSE, Kalasalingam University, Srivilliputtur, Tamilnadu, India
Vishnu Gupta
Department of CSE, Kalasalingam University, Srivilliputtur, Tamilnadu, India

Search engine, crawling, spiders, building an index, API key, ranking factors.

  1. Feng Zhao, Jingyu Zhou, Chang Nie, Heqing Huang, Hai Jin, "SmartCrawler: A Two- Stage Crawler forEfficiently Harvesting Deep-Web Interfaces", IEEE Transaction on? services computing, Vol-99, 2015.
  2. M. Burner, "Crawling towards Eternity: Building an Archive of the World Wide Web,” Web Techniques Magazine, vol. 2, pp. 37-40, 1997.
  3. Allan Heydon and Marc Najork, Mercator: A scalable,extensible webcrawler. World Wide Web Conference,2(4):219?229, April 1999.
  4. Jenny Edwards, Kevin S. McCurley, and John A. Tomlin. An adaptive model for optimizing performance of an incremental web crawler. In Proceedings of the Tenth Conference on World Wide Web, pages 106?113, Hong Kong, May 2001. Elsevier Science.
  5. Luciano Barbosa and Juliana Freire. Searching for hidden-web databases. In WebDB, pages 1? 6, 2005.
  6. Soumen Chakrabarti, Martin Van den Berg, and Byron Dom. Focused crawling: a new approach to topic-specific web re-source discovery. Computer Networks, 31(11):1623?1640, 1999.
  7. Jayant Madhavan, David Ko, ?ucja Kot, Vignesh Ganapathy, Alex Rasmussen, and Alon Halevy. Google’s deep web crawl. Proceedings of the VLDB Endowment, 1(2):1241?1252, 2008.
  8. Olston Christopher and Najork Marc. Web crawling. Foundations and Trends in Information Retrieval, 4(3):175?246, 2010.
  9. Balakrishnan Raju and Kambhampati Subbarao. Sourcerank:Relevance and trust assessment for deep web sources based on inter-source agreement. In Proceedings of the 20th international conference on World Wide Web, pages 227?236, 2011.
  10. Denis Shestakov and Tapio Salakoski. On estimating the scale of national deep web. InDatabase and Expert Systems Applications, pages 780?789. Springer, 2007M.K.Sherbiny El “Efficient fuzzy logic load frequency controller”Energy Conversion and Management 43(2002)1853-1863 Elsevier

Publication Details

Published in : Volume 3 | Issue 5 | May-June 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 183-186
Manuscript Number : ICASCT2530
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

S. Dhanasekaran, Vamshikrishna Bandari, Ravi Teja, Vishnu Gupta, " A Smart Searching Technique for Optimizing Relevant Web portal Discovery, International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 5, pp.183-186, May-June-2017. Available at doi : 10.32628/ICASCT2530
Journal URL : http://ijsrst.com/ICASCT2530

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