Machine Learning as a New Search Engine Interface: An Overview

Authors

  • Taposh Kumar Neogy IBA (National University), Rajshahi
  • Harish Paruchuri University of Houston-Clear Lake

DOI:

https://doi.org/10.18034/ei.v2i2.539

Keywords:

Machine Learning, Search Engine Interface, Search Technology

Abstract

The essence of a web page is an inherently predisposed issue, one that is built on behaviors, interests, and intelligence. There are relatively a ton of reasons web pages are critical to the new world, as the matter cannot be overemphasized. The meteoric growth of the internet is one of the most potent factors making it hard for search engines to provide actionable results. With classified directories, search engines store web pages. To store these pages, some of the engines rely on the expertise of real people. Most of them are enabled and classified using automated means but the human factor is dominant in their success. From experimental results, we can deduce that the most effective and critical way to automate web pages for search engines is via the integration of machine learning.

 

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Author Biographies

  • Taposh Kumar Neogy, IBA (National University), Rajshahi

    Assistant Professor (Accounting), Institute of Business Administration (IBA), National University, Rajshahi, BANGLADESH

  • Harish Paruchuri, University of Houston-Clear Lake

    Department of Computing Sciences, University of Houston-Clear Lake, 2700 Bay Area Blvd, Houston, TX 77058, USA

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Published

2014-12-31

Issue

Vol. 2 No. 2 (2014): July - December

Section

Peer Reviewed Articles

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How to Cite

Neogy, T. K. ., & Paruchuri, H. (2014). Machine Learning as a New Search Engine Interface: An Overview. Engineering International, 2(2), 103-112. https://doi.org/10.18034/ei.v2i2.539