Recommending Books for Children Based on the Collaborative and Content-Based Filtering Approaches

Abstract

According to a study conducted by the National Institute of Child Health and Human Development, reading is the single most important skill necessary for a happy, productive, and successful life. A child who is an excellent reader often has confident and a high level of self esteem and can easily make the transition from learning to read to reading to learn. Promoting good reading habits among children is essential, given the enormous influence of reading on students’ development as learners and members of the society. Unfortunately, very few (children) websites or online applications recommend books to children, even though they can play a significant role in encouraging children to read. Popular book websites, such as goodreads.com, commonsensemedia.org, and readanybook.com, suggest books to children based on the popularity of books or rankings on books, which are not customized/personalized for each individual user and likely recommend books that users do not want or like. We have integrated the collaborative filtering (CF) approach and the content-based approach, in addition to predicting the grade levels of books, to recommend books for children. The user-based CF approaches filter books appealing to each user based on users’ ratings, whereas the content-based filtering method analyzes the descriptions of books rated by a user in the past and constructs a user profile to capture the user’s preferences. Recent research works have demonstrated that a hybrid approach, which combines the content-based filtering and CF approaches is more effective in making recommendations. Conducted empirical study has verified the effectiveness of our proposed children book recommender.