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Ontology-based recommendation involving consumer product reviews

机译:基于本体的推荐,涉及消费品评论

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The rapid development of internet, stimulates the development of e-commerce sites. Generally, an e-commerce site provides some review pages, which are collections of reviews from the users of the product. The reviews are useful for a prospective buyer, as consideration for purchasing products. In addition, the recommender system has evolved as a tool for prospective buyers in obtaining the desired product. Most of prior works on knowledge-based recommender system area, utilize recommendation techniques that are based on product features. In this paper, we elaborate the product reviews into the recommendation technique, in addition to product features. Many customers are not familiar with the technical features of the product (e.g. smartphones, cars, cameras, notebooks, etc), so that in our proposed framework, preferences of customers (users) is expressed in the form of functional requirements of products. Mapping the functional requirements - product features - product reviews are in ontology, so the recommendation is based on the exploration of semantic relations in this ontology. To evaluate user's perception of our proposed framework, we compare our proposed framework with a recommender system based on product features (without involving the product reviews), using the Technology Acceptance Model (TAM). Based on evaluation results, we conclude that involving product reviews on recommender system able to increase perceived usefulness and perceived ease of use. In addition, recommender system involving product reviews is more acceptable than recommender system that does not involve product reviews.
机译:互联网的飞速发展,刺激了电子商务网站的发展。通常,电子商务站点提供一些评论页面,这些页面是来自产品用户的评论的集合。这些评论对于潜在的购买者很有用,可以作为购买产品的考虑因素。另外,推荐系统已经发展成为潜在购买者获得所需产品的工具。在基于知识的推荐器系统领域,大多数先前的工作都利用基于产品功能的推荐技术。在本文中,除了产品功能之外,我们还将产品评论详细介绍到推荐技术中。许多客户不熟悉产品的技术功能(例如智能手机,汽车,照相机,笔记本电脑等),因此在我们建议的框架中,客户(用户)的偏好以产品功能需求的形式表达。映射功能需求-产品功能-产品评论位于本体中,因此建议基于对该本体中语义关系的探索。为了评估用户对我们提出的框架的看法,我们使用技术接受模型(TAM)将我们提出的框架与基于产品功能(不涉及产品评论)的推荐系统进行比较。根据评估结果,我们得出结论,在推荐系统上进行产品审查,能够提高感知的实用性和感知的易用性。另外,涉及产品评论的推荐系统比不涉及产品评论的推荐系统更容易接受。

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