Personalized Recommender System for Children's Book Recommendation with a Real-Time Interactive Robot

Abstract

In this paper we study the personalized book recommender system in a child–robot interactive environment. Firstly, we propose a novel text search algorithm using an inverse filtering mechanism that improves the efficiency. Secondly, we propose a user interest prediction method based on the Bayesian network and a novel feedback mechanism. The feedback is processed by converting the user’s reaction into accept or reject. According to children's fuzzy language input, the proposed method gives the predicted interests, which is based on a common set of interests related to children's literature. Thirdly, the domain specific synonym association is proposed based on word vectorization, in order to improve the understanding of user intention. Additional phrases are extended to broaden the user's search range. Experimental results show that the proposed recommender system has an improved performance compared with the baseline results. Due to the algorithm efficiency design, it can operate on embedded consumer devices with limited computational resources.

Received: 15 March 2023 | Revised: 11 April 2023 | Accepted: 28 April 2023

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

The data that support the findings of this study are not publicly available due to involvement with commercial products.

Author Contribution Statement

Yun Liu: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization. Tianmeng Gao: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization. Baolin Song: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization. Chengwei Huang: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.