Abstract Recommender systems are cognitive computing systems designed to support humans in their decision-making processes through convincing, timely product suggestions. In the field of recommender systems, critique-based recommenders have been widely applied as an effective approach for guiding users through a product space in pursuit of suitable products. To date, no critique-based approach has included an assistant that support users in their search in a pleasant way. In this paper, we describe how we integrate an assistant within a critique-based recommender. We consider the proposed assistant to be cognitive because its reasoning process when recommending products is based on a cognitively-inspired clustering algorithm. The proposal is evaluated by users and compared with a non-assistant approach. The results of this research demonstrate that the integration of a cognitive assistant within the recommender improves the user experience and increases the performance of the recommendation process, i.e., users need fewer cycles to achieve the desired product or service.

中文翻译：

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在基于评论的推荐系统中集成认知助手

摘要 推荐系统是一种认知计算系统，旨在通过令人信服、及时的产品建议来支持人类的决策过程。在推荐系统领域，基于评论的推荐系统作为引导用户通过产品空间寻找合适产品的有效方法已被广泛应用。迄今为止，还没有基于评论的方法包括以愉快的方式支持用户搜索的助手。在本文中，我们描述了如何将助手集成到基于评论的推荐系统中。我们认为所提出的助手是认知的，因为它在推荐产品时的推理过程是基于受认知启发的聚类算法。该提案由用户评估并与非辅助方法进行比较。