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A new approach for item ranking based on review scores reflecting temporal trust factor

Citation

Saito, K and Kimura, M and Ohara, K and Motoda, H, A new approach for item ranking based on review scores reflecting temporal trust factor, Social Computing, Behavioral-Cultural Modeling, and Prediction, 7th International Conference, SBP 2014, 1-4 April 2014, Washington, DC, USA, pp. 161-168. ISSN 0302-9743 (2014) [Refereed Conference Paper]

Copyright Statement

Copyright 2014 Springer International Publishing Switzerland

Official URL: http://dx.doi.org/10.1007/978-3-319-05579-4_20

Abstract

We propose a new item-ranking method that is reliable and can efficiently identify high-quality items from among a set of items in a given category using their review-scores which were rated and posted by users. Typical ranking methods rely only on either the number of reviews or the average review score. Some of them discount outdated ratings by using a temporal-decay function to make a fair comparison between old and new items. The proposed method reflects trust levels by incorporating a trust discount factor into a temporal-decay function. We first define the MTDF (Multinomial with Trust Discount Factor) model for the review-score distribution of each item built from the observed review data. We then bring in the notion of z-score to accommodate the trust variance that comes from the number of reviews available, and propose a z-score version of MTDF model. Finally we demonstrate the effectiveness of the proposed method using the MovieLens dataset, showing that the proposed ranking method can derive more reasonable and trustable rankings, compared to two naive ranking methods and the pure z-score based ranking method.

Item Details

Item Type:Refereed Conference Paper
Keywords:item-ranking, trust discount factor, Z-score
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Artificial Intelligence and Image Processing not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Computer Software and Services not elsewhere classified
Author:Motoda, H (Dr Hiroshi Motoda)
ID Code:89000
Year Published:2014
Deposited By:Computing and Information Systems
Deposited On:2014-02-22
Last Modified:2017-11-18
Downloads:0

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