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Design of a Recommendation Model Considering Semantic Analysis

by Umasankar Das, Girija Prasad Mohapatra, Vinay Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 1
Year of Publication: 2013
Authors: Umasankar Das, Girija Prasad Mohapatra, Vinay Kumar
10.5120/13362-0956

Umasankar Das, Girija Prasad Mohapatra, Vinay Kumar . Design of a Recommendation Model Considering Semantic Analysis. International Journal of Computer Applications. 77, 1 ( September 2013), 45-49. DOI=10.5120/13362-0956

@article{ 10.5120/13362-0956,
author = { Umasankar Das, Girija Prasad Mohapatra, Vinay Kumar },
title = { Design of a Recommendation Model Considering Semantic Analysis },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 1 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 45-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number1/13362-0956/ },
doi = { 10.5120/13362-0956 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:50:21.982881+05:30
%A Umasankar Das
%A Girija Prasad Mohapatra
%A Vinay Kumar
%T Design of a Recommendation Model Considering Semantic Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 1
%P 45-49
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Social networking site is increasingly used as a channel for reaching end users. Personalized Recommender system can work on participatory media content and enhance CMC (computer mediated communication) ultimately providing the user with the finest items of interest. It collects data implicitly as well as explicitly and takes into consideration user activity, preferences, and ratings to evaluate weights for calculation of trust, social intimacy, popularity and semantic scores. The accumulation of these scores generates the final recommendation score and based on it a recommendation list is generated for each user . Several important theories in this regard have proven to be viable and some not so feasible. Thus comparative study of some recommendation systems can throw light on the problems faced and suggest solutions in this regard.

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Index Terms

Computer Science
Information Sciences

Keywords

Social Networking Participatory Media Personalized Recommender system Semantic Trust.

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