Proposal and Evaluation of Serendipitous Recommendation Method Using General Unexpectedness
Proposal and Evaluation of Serendipitous Recommendation Method Using General Unexpectedness
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发表时间：
2010
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通讯作者：
Takayuki Akiyama;Kiyohiro Obara;M. Tanizaki
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作者：
Takayuki Akiyama;Kiyohiro Obara;M. Tanizaki
系统支持用户在信息丰富的环境中选择项目和服务。尽管推荐系统在准确性方面已经得到了改进，但是这样的系统在新颖性和偶然性方面仍然不足，给用户带来了不满意的结果。因此，提出了两种"偶然推荐"的方法。然而，还不存在用于向用户准确地推荐偶然项目的方法，因为没有明确定义什么类型的项目是偶然的。因此，人类的偏好模型的偶然项目的实际数据的基础上收集的用户的印象问卷设计。设计了两种基于该模型的偶然性推荐方法，并根据用户的实际印象进行了评价。评估结果表明，其中一种推荐方法，即独立于用户个人资料的一般意外性推荐方法，可以准确地推荐偶然发现的项目。
systems support users in selecting items and services in an information-rich environment. Although recommender systems have been improved in terms of accuracy, such systems are still insufficient in terms of novelty and serendipity, giving unsatisfactory results to users. Two methods of "serendipitous recommendation" are therefore proposed. However, a method for recommending serendipitous items accurately to users does not yet exist, because what kinds of items are serendipitous is not clearly defined. Accordingly, a human preference model of serendipitous items based on actual data concerning a user's impression collected by questionnaires was devised. Two serendipitous recommendation methods based on the model were devised and evaluated according to a user's actual impression. The evaluation results show that one of these recommendation methods, the one using general unexpectedness independent of user profiles, can recommend the serendipitous items accurately.