Paper Info
Title
Analysis Of Mood Tags For Multimedia Content Recommendation In Social Networks
Abstract
The propensity of Web information purchasers is changing from cost effectiveness that emphasizes price with performance to cost satisfaction that emphasizes purchaser's psychological satisfaction. One of the methods to improve user's cost satisfaction in recommending multimedia contents is to use mood inherent in multimedia contents. SNS services based on mood folksonomy are applications using such a method. However, in the applications based on folksonomy, the problem caused by synonyms exists. This paper suggests a cost-satisfactive multimedia contents recommendation method to solve the problem on synonym. To this end, we utilizes the value of Arousal & Valence which express mood of multimedia content as its internal tag. A method that defines the relation between AV values of multimedia contents and AV values of mood tags is suggested by considering synonym and the correlation between them is analyzed. From the analysis, it is shown that the AV values of multimedia contents with a mood tag and its synonyms reside in the area of the mood tag in the Thayor model.
Year
DOI
Venue
2019
10.1109/ICUFN.2019.8806025
2019 ELEVENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN 2019)
Keywords
Field
DocType
multimedia content, cost satisfaction, multimedia content mood, multimedia content recommendation, mood tag, social network
Mood,Social network,Computer science,Folksonomy,Web information,Multimedia
Conference
ISSN
Citations 
PageRank 
2165-8528
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Chang Bae Moon102.37
Jong Yeol Lee202.03
Dong-Seong Kim36428.80
Byeong Man Kim427720.88