Paper Title

Literature survey on user action interpretation and content recommendation

Authors

  • Surabhi Bhagat
  • Mahesh Katre

Keywords

Content optimization, recommendation models, personalized systems, action interpretation, user segmentation

Abstract

Today, millions of user interacts with the search engines to get acquainted with the latest trends. System requires timely updates to ensure that the users get up to date news or advertisements. Instead of digging for a linked search, the system must provide a recommender system which provides with a column of articles related to the users’ search. This can lead to online content optimization. User interaction plays a key role in optimizing the contents of a website. User profiles can be created with the adaptive web pages displaying the recommended contents based on feedback. It is impossible to capture all the contents and display according to the user’s need and thus challenges come across. Personalized web portal services need to be taken a deeper look for content optimization. User Interactions should be managed and applied to the web portals using recommendation models. Recommendation models prove to be significant in online content optimization. The results of an adaptive system are carried out on real user traffic.

Article Type

Published

How To Cite

Surabhi Bhagat, Mahesh Katre. "Literature survey on user action interpretation and content recommendation".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.4, Issue 2, pp.210-213, URL :https://rjwave.org/ijedr/papers/IJEDR1602036.pdf

Issue

Volume 4 Issue 2 

Pages. 210-213

Article Preview