Research on Mechanism and Challenges in Meta Search Engines
Jyoti Mor1, Naresh Kumar2, Dinesh Rai3
1Jyoti Mor1, Phd. Research Scholar, Computer Science, School of Engineering and Technology, Ansal University, Gurugram, India.
2Dr. Naresh Kumar, Associate Professor, Dept. of Computer Science & Engineering, MSIT, New De,lhi, India.
3Dr. Dinesh Rai, Associate Professor, School of Engineering and Technology, Ansal University, Gurugram, India.
Manuscript received on 09 August 2019 | Revised Manuscript received on 16 August 2019 | Manuscript Published on 31 August 2019 | PP: 281-284 | Volume-8 Issue-9S2 August 2019 | Retrieval Number: I10570789S219/19©BEIESP DOI: 10.35940/ijitee.I1057.0789S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A Meta Search Engine (MSE) produces results gathered from other search engine (SE) on a given query. In brief MSEs have single interface corresponding to multiple searches. MSE employs their own algorithm to display search results. This paper reviews existing Meta Search Engines like Yippy, eTools.ch, Carrot2, qksearch and iBoogie commonly used for searching. This paper surveys and analysed the working of different result merging algorithms. Current research reviews MSE based on different approaches like clustering technique. Few MSEs are employing Neural networks for searching. Further it also discusses problem in existing MSEs.
Keywords: Search Engine, Meta Search Engine, Web page, Clustering
Scope of the Article: Computational Techniques in Civil Engineering