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PSEFiL: A Personalized Search Engine with Filtered Links

by Hajar Aghaiipour-chafuchahi, Fatemeh Ahmadi-abkenari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 110 - Number 6
Year of Publication: 2015
Authors: Hajar Aghaiipour-chafuchahi, Fatemeh Ahmadi-abkenari
10.5120/19323-0961

Hajar Aghaiipour-chafuchahi, Fatemeh Ahmadi-abkenari . PSEFiL: A Personalized Search Engine with Filtered Links. International Journal of Computer Applications. 110, 6 ( January 2015), 34-40. DOI=10.5120/19323-0961

@article{ 10.5120/19323-0961,
author = { Hajar Aghaiipour-chafuchahi, Fatemeh Ahmadi-abkenari },
title = { PSEFiL: A Personalized Search Engine with Filtered Links },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 110 },
number = { 6 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume110/number6/19323-0961/ },
doi = { 10.5120/19323-0961 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:45:40.577272+05:30
%A Hajar Aghaiipour-chafuchahi
%A Fatemeh Ahmadi-abkenari
%T PSEFiL: A Personalized Search Engine with Filtered Links
%J International Journal of Computer Applications
%@ 0975-8887
%V 110
%N 6
%P 34-40
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The dynamic nature of the World Wide Web and its growing dimension make retrieving the exact information a difficult task. Inaccurate answers delivered by search engines especially for the query phrases with different meaning makes the feeling of dissatisfaction in today's surfers who needs the specific answer for their information demand. Search engines nowadays tries to understand users' request through studying his/her search background or even make users participate in the search process in order to clarify what he/she really needs. This trend is part of the search engines' endeavors to become personalized. One of the well-formed personalized search engines is SNAKET that employs the user participation for personalization process. In this paper based on the personalization algorithm of SNAKET, we propose an architecture of our personalized search engine of PSEFiL that filters out the links and delivers the answers to users with low or no content drift as a means of enriching the answer set. Furthermore, the answer set is robust because every existing link in result set either is highly ranked from other search engines or has no or less subject jumps with an exact manual scan process. Also every link is clearly classified to every fetched meaning of a query phrase. One objective of PSEFiL is to give the accurate answers not to populate the answer set with more links that may contain less or no accurate answers.

References
  1. Ahmadi-Abkenari, F. , Selamat, A. 2012. "An Architecture for a Focused Trend Parallel Web Crawler with the Application of Clickstream Analysis", International Journal of Information Sciences, Elsevier, Vol. 184, pp. 266-281.
  2. Ahmadi-Abkenari, F. , and Selamat, A. 2013. "Advantages of Employing LogRank Web Page Importance Metric in Domain Specific Web Search Engines". JDCTA: International Journal of Digital Content Technology and its Applications. Vol. 7, No. 9. pp. 425-432.
  3. Ahmadi-Abkenari, F. , and Selamat, A. 2012. "LogRank: A Clickstream-based Web Page Importance Metric for Web Crawlers". JDCTA: International Journal of Digital Content Technology and its Applications. Vol. 6, No. 1. pp. 200-207.
  4. Alhalabi W. , Kubat M. and Tapia M. 2006. "Search Engine Personalization Tool Using Linear Vector Algorithm". Proceedings of the 4th Saudi Technical Conference and Exhibition. pp. 336-344.
  5. Baeza R. and Boldi, P. 2010. "Advanced Techniques in Web Intelligence". Studies in Computational Intelligence. Vol. 311. pp. 113-142.
  6. Ferragina P. and Gulli A. 2005. "A Personalized Search Engine Based on Web Snippet Hierarchical Clustering". In proceedings of the World Wide Web Conference, Japan. pp. 801-810.
  7. Husin H. S, Thom J. A and Zhang X. 2013. "News Recommendation Based on Web Usage and Web Content Mining". Data Engineering Workshops (ICDEW), IEEE 29th. pp. 326 – 329.
  8. Kim K. J. , Cho S. B. 2005. "Personalized mining of Web documents using link structures and fuzzy concept networks". Applied Soft Computing 7. Elsevier. pp. 398–410.
  9. Kumar S. and Devi N. 2010 "Learner's Centric Approach for Web Mining". International Journal of Computer Science and Information Technologies (IJCSIT). Vol. 1(2).
  10. Liu B. , Mobasher, B. and Nasraoui O. 2011. "Web Data Mining Data-Centric Systems and Applications". pp. 527-603.
  11. Markov, L. 2007. "Data Mining the Web". Wiley Publication. Chapter 6, 7, 8. pp. 143-188.
  12. Nyein, S. S. 2011. "Mining Contents in Web page using Cosine Similarity". Computer Research and Development (ICCRD). IEEE. Vol. 2. pp. 472 – 475.
  13. Sharma K. , Shrivastava G. and Kumar V. 2011. "Web Mining: Today and Tomorrow". The 3rd International Conference of Electronics Computer Technology (ICECT), Vol. 1. pp. 399 – 403.
  14. Souldatos S. , Dalamagas T. and Sellis T. 2006. "Captain Nemo: A Meta-Search Engine with Personalized Hierarchical Search Space", INFORMATICA. Vol. 30. pp. 173-182.
  15. Srikantaiah K. C. , Suraj M. , Venugopal K. R. , Iyengar S. S. and Patnaik L. M. 2012. "Similarity Based Web Data Extraction and Integration System for Web Content Mining". Advances in Communication and Computing. Springer. Vol. 108. pp. 269-274.
Index Terms

Computer Science
Information Sciences

Keywords

Search engine Search engine optimization Search engine personalization Web Structure Mining.

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