Open Access   Article Go Back

Architecture for Personalized Meta Search Engine

N. A. Borkar1 , S. V. Kulkarni2

Section:Research Paper, Product Type: Journal Paper
Volume-06 , Issue-01 , Page no. 55-59, Feb-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6si1.5559

Online published on Feb 28, 2018

Copyright © N. A. Borkar, S. V. Kulkarni . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: N. A. Borkar, S. V. Kulkarni, “Architecture for Personalized Meta Search Engine,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.01, pp.55-59, 2018.

MLA Style Citation: N. A. Borkar, S. V. Kulkarni "Architecture for Personalized Meta Search Engine." International Journal of Computer Sciences and Engineering 06.01 (2018): 55-59.

APA Style Citation: N. A. Borkar, S. V. Kulkarni, (2018). Architecture for Personalized Meta Search Engine. International Journal of Computer Sciences and Engineering, 06(01), 55-59.

BibTex Style Citation:
@article{Borkar_2018,
author = {N. A. Borkar, S. V. Kulkarni},
title = {Architecture for Personalized Meta Search Engine},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2018},
volume = {06},
Issue = {01},
month = {2},
year = {2018},
issn = {2347-2693},
pages = {55-59},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=191},
doi = {https://doi.org/10.26438/ijcse/v6i1.5559}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i1.5559}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=191
TI - Architecture for Personalized Meta Search Engine
T2 - International Journal of Computer Sciences and Engineering
AU - N. A. Borkar, S. V. Kulkarni
PY - 2018
DA - 2018/02/28
PB - IJCSE, Indore, INDIA
SP - 55-59
IS - 01
VL - 06
SN - 2347-2693
ER -

           

Abstract

Information available on the web is growing rapidly. A major problem in web search is that the interactions between the users and search engines are limited by the factors like unknown capabilities of search engines adopted, and ill-constructed query by the user. Hence the user has to repeatedly apply the several queries till he reaches the pages of most interest. Any search engine can give its best performance if well-constructed and detailed queries are used. As a result, the users tend to submit shorter/ insufficient/ ambiguous queries yielding unwanted search lists. In order to return highly relevant results to the users, search engines must be able to profile the users’ interests and personalize the search results according to the users’ profiles. This paper discusses the need and specific requirements of personalized search engine, its architecture, the prototype model developed and the results obtained. Also sample sessions performed on the designed model have been given for selected user profile.

Key-Words / Index Term

Web Search Engines, Personalized Web Searching, Meta Search Engines

References

[1] K Wai-Ting Leung, D Lee, W Lee, “PMSE: A Personalized Mobile Search Engine”, IEEE Transactions On Knowledge And Data Engineering, Vol. 25, Issue: 4, pp.820-834, April 2013.
[2] S. Prakasha, H.Shashidhar, G.T. Raju, “Structured Intelligent Search Engine for Effective Information Retrieval using Query Clustering Technique and Semantic Web”, International Conference on Contemporary Computing and Informatics (IC3I), 688 695, DOI: 10.1109/IC3I.2014.7019820.
[3] A Annadurai, “Architecture of personalized web search engine using suffix tree clustering”, International Conference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN 2011), pp. 604-608, 2011.
[4] K.W.-T. Leung, W. Ng, and D.L. Lee, “Personalized Concept-Based Clustering of Search Engine Queries,” IEEE Trans. Knowledge and Data Eng., vol. 20, no. 11, pp. 1505-1518, Nov. 2008.
[5] J. Teevan, S.T. Dumais, and E. Horvitz., “Personalizing Search via Automated Analysis of Interests and Activities. Proceedings of the 28th Annual International ACM SIGIR” Conference on Research and development in information retrieval (SIGIR`05), pages 449–456, 2005.
[6] Adah, S.; Bufi, C.; Temtanapat, Y., “Integrated Search Engine”, @IEEE Knowledge and Data Engineering Exchange Workshop, 1997. Pages: 140 – 147.
[7] O. Zamir, O.Etzioni, “A Dynamic Clustering interface to Web search results,” Computer Networks, Netherlands, Amsterdam, 31(11-16):1361-1374, 1999.
[8] M. Ilic, P. Spalevic, M. Veinovic, “Suffix Tree Clustering – Data mining algorithm”, Twenty-Third International Electrotechnical and Computer Science Conference ERK`2014, Portorož, ISSN 1581-4572, pp. 15-18, September 22-24, 2014.
[9] K A Heller, Z Ghahramani. “Bayesian hierarchical clustering”, Proceedings of the 22nd international conference on Machine learning, pp. 297-304, 2005.
[10] R.E. Ruviaro Christ, E. Talavera, C. Maciel, “Gaussian Hierarchical Bayesian Clustering Algorithm”, ISDA 2007, pp. 133-13.