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Application of Recommendation System on Semantic based Matching Approach

by Jayashree Salunke, Anagha Chaudhari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 14
Year of Publication: 2018
Authors: Jayashree Salunke, Anagha Chaudhari
10.5120/ijca2018917662

Jayashree Salunke, Anagha Chaudhari . Application of Recommendation System on Semantic based Matching Approach. International Journal of Computer Applications. 181, 14 ( Sep 2018), 5-8. DOI=10.5120/ijca2018917662

@article{ 10.5120/ijca2018917662,
author = { Jayashree Salunke, Anagha Chaudhari },
title = { Application of Recommendation System on Semantic based Matching Approach },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2018 },
volume = { 181 },
number = { 14 },
month = { Sep },
year = { 2018 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number14/29888-2018917662/ },
doi = { 10.5120/ijca2018917662 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:05:56.730264+05:30
%A Jayashree Salunke
%A Anagha Chaudhari
%T Application of Recommendation System on Semantic based Matching Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 14
%P 5-8
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A recommendation system is a software program which endeavours to limit determinations for clients in light of their communicated inclinations, past behaviour, or other information which can be mined about the client or different clients with similar interests. This paper proposes a new personalized recommendation model or personalized academic knowledge sharing system based on domain knowledge to emphasize the importance of domain knowledge in recommendation process. We explore user profiling within recommender systems, working on the problem of recommending academic users or employees to share his/her knowledge. We propose a one of a kind semantic based matching approach to portray the similarity of academic employees to share and improve his/her knowledge. This system recommends the persons who have deep knowledge of the domain and research interest appropriately as compare to other state of art system. We used here text mining for extract the research interest.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Academic knowledge sharing system Recommendation System Semantic based Matching Approach Text Mining

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