On Affinity Measures for Artificial Immune System Movie Recommenders

U. Aickelin, Qi Chen
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引用次数: 10

Abstract

We combine Artificial Immune Systems 'AIS', technology with Collaborative Filtering 'CF' and use it to build a movie recommendation system. We already know that Artificial Immune Systems work well as movie recommenders from previous work by Cayzer and Aickelin 3, 4, 5. Here our aim is to investigate the effect of different affinity measure algorithms for the AIS. Two different affinity measures, Kendalls Tau and Weighted Kappa, are used to calculate the correlation coefficients for the movie recommender. We compare the results with those published previously and show that Weighted Kappa is more suitable than others for movie problems. We also show that AIS are generally robust movie recommenders and that, as long as a suitable affinity measure is chosen, results are good.
人工免疫系统电影推荐的亲和度量研究
我们将人工免疫系统(AIS)、协同过滤技术(CF)结合起来,构建了一个电影推荐系统。从Cayzer和Aickelin之前的研究中,我们已经知道人工免疫系统作为电影推荐器的效果很好。在这里,我们的目的是研究不同的亲和度量算法对AIS的影响。使用肯德尔Tau和加权Kappa两种不同的亲和度量来计算电影推荐的相关系数。我们将结果与先前发表的结果进行了比较,结果表明加权Kappa比其他方法更适合于电影问题。我们还表明,AIS通常是稳健的电影推荐器,只要选择合适的亲和度量,结果就很好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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