Document recommendation in social tagging services
Proceedings of the 19th international conference on World wide web
ReadAid: A Robust and Fully-Automated Readability Assessment Tool
ICTAI '11 Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
BReK12: a book recommender for K-12 users
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Booksonline'12: 5th workshop on online books, complementary social media and their impact
Proceedings of the 21st ACM international conference on Information and knowledge management
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Learning to read efficiently and effectively is emphasized at the elementary and high school levels. Finding books that children/youth are interested in reading, however, is a non-trivial task due to the diversity of topics and different readability levels covered in the huge volume of books available these days. Ideally, K-12 students can turn to book recommenders which suggest books that match their interests. However, since the preferences and reading levels of these students vary from one grade to another, books suggested by existing recommenders, which ignore the literacy skills and the personal interests of their users, may be unsuitable for the targeted audience. In this paper, we present additional design issues that should be applied in developing a book recommender based on BReK12, our previously-proposed book recommender for K-12 users, to further enhance the quality of its recommendations. BReK12, which performs content and readability analysis to identify books potentially appealing to its users, is extended to incorporate (i) a multi-criteria analysis that studies its users' complex and diverse interests and (ii) an enhanced readability-detection tool that determines precisely the readability levels of books which match the literary skills of its users.