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Reseach Article

Family Aware TV Program and Settings Recommender

by Thyagaraju GS, Umakant P Kulkarni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 29 - Number 4
Year of Publication: 2011
Authors: Thyagaraju GS, Umakant P Kulkarni

Thyagaraju GS, Umakant P Kulkarni . Family Aware TV Program and Settings Recommender. International Journal of Computer Applications. 29, 4 ( September 2011), 1-18. DOI=10.5120/3556-4889

@article{ 10.5120/3556-4889,
author = { Thyagaraju GS, Umakant P Kulkarni },
title = { Family Aware TV Program and Settings Recommender },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 29 },
number = { 4 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 1-18 },
numpages = {9},
url = { },
doi = { 10.5120/3556-4889 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:14:52.779286+05:30
%A Thyagaraju GS
%A Umakant P Kulkarni
%T Family Aware TV Program and Settings Recommender
%J International Journal of Computer Applications
%@ 0975-8887
%V 29
%N 4
%P 1-18
%D 2011
%I Foundation of Computer Science (FCS), NY, USA

In this paper we are proposing a design of TV program and settings recommendation engine utilizing contextual parameters like personal, social, temporal, mood and activity. In addition to the contextual parameters the system utilize the explicit or implicit user ratings and watching history to resolve the conflict if any while recommending the services .The System is implemented exploiting AI techniques ( like ontology, fuzzy logic ,Bayesian classifier and Rule Base) , RDBMS and SQL Query Processing . The motivation behind the proposed work is i) to improve the user’s satisfaction level and ii) to improve the social relationship between user and TV. The context aware recommender utilizes social context data as an additional input to the recommendation task alongside information of users and tv programs. We have analyzed the recommendation process and performed a subjective test to show the usefulness of the proposed system for small families.

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Index Terms

Computer Science
Information Sciences


Ubiquitous context recommendation engine conflict context aware tv family preference role age social status favorite program automatic fuzzy logic mood activity