A Relational Recommender System Based on Domain Ontology

Hikmet Kapusuzoglu, Ş. Öğüdücü
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引用次数: 8

Abstract

Product recommendation on electronic commerce Web sites becomes more important with the widespread use of Internet-based shopping. Collaborative filtering and content based filtering methods have been commonly used for this task by electronic commerce Web sites. These methods have several shortcomings, such as cold start problem, biased ratings problem or inaccurate recommendations. In order to produce effective and accurate recommendations, recent approaches utilize the semantic properties of data by integrating the domain ontology into the recommendation process. In these studies, the domain ontology covering only the types and properties of the product to be recommended is considered where the relational nature of the product data is omitted. However, the domain ontology of the features related to the product may also provide useful information during recommendation process. In this study, we focus on integrating the domain ontology of relational data into the recommendation process. We design a framework for an easy implementation of a recommendation system on relational data. Using this framework, we implement as a case study a recommendation model that recommends books to the users. We evaluated the performance of our model on real data obtained from a Turkish Internet book store. Our experimental results show that our proposed method can be effectively used for recommending items in relational data.
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基于领域本体的关系推荐系统
随着网络购物的广泛使用,电子商务网站上的产品推荐变得越来越重要。电子商务网站通常使用协作过滤和基于内容的过滤方法来完成此任务。这些方法存在冷启动问题、评分偏差问题或推荐不准确等缺点。为了产生有效和准确的推荐,最近的方法通过将领域本体集成到推荐过程中来利用数据的语义属性。在这些研究中,只考虑涵盖被推荐产品的类型和属性的领域本体,而忽略了产品数据的关系性质。然而,与产品相关的特征的领域本体也可能在推荐过程中提供有用的信息。在本研究中,我们的重点是将关系数据的领域本体集成到推荐过程中。我们设计了一个基于关系数据的推荐系统的简单实现框架。使用这个框架,我们实现了一个向用户推荐书籍的推荐模型作为案例研究。我们对从土耳其网络书店获得的真实数据进行了模型性能评估。实验结果表明,该方法可以有效地用于关系数据中的项目推荐。
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