International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 136 | Views: 183

Research Paper | Computer Science & Engineering | Ethiopia | Volume 6 Issue 3, March 2017

Fast Prototyping Networks and Using Datamining Applications

Tewhasom Aregay Weldu [2]

Abstract: To study different applications of mining for the fast prototyping networks and improvement of search engine ranking, network information retrieval and fast prototyping network environment enhancement. The advantage of the implicit feedback left in the trail of users while navigating through fast prototyping networks. The value of queries to extract interesting rules, patterns and information about the documents they reach. The models, created in this Paper work, show that the wisdom of the crowds conveyed in queries has many applications that overall provide a better understanding of users needs in the fast prototyping network. The general interaction of applications with fast prototyping networks and searching engines in a straightforward way. We focus our efforts on analyzing and extracting valuable knowledge from the behavior of users on the fast prototyping networks. Much of this information is provided implicitly by users and recorded in usage logs, which include search engine query logs and/or network access logs. In particular, we center our research on queries that users submit to fast prototyping search engines, which we believe convey in straight forward way wisdom of the crowds. The intuition is that queries and their clicked results implicitly convey the opinion of users about specific network documents. As discuss throughout this paper, queries are crucial to understanding how users interact with Web sites and search engines. Implicit user feedback provides a unique insight into users actual needs on the Web.

Keywords: Wisdom of the crowds, fast prototyping, search engines, websites, Network data mining

Edition: Volume 6 Issue 3, March 2017,

Pages: 564 - 568

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