ABSTRACT
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.
- G. Adomavicius, N. Manouselis, and Y. Kwon. Recom- mender Systems Handbook, chapter Multi-Criteria Recommender Systems, pages 769--803. Springer, 2011.Google Scholar
- G. French. Children's early learning and development: Background paper for the framework for early learning. Paper Commissioned by the National Council for Curriculum and Assessment, 2007.Google Scholar
- Z. Guan, C. Wang, J. Bu, C. Chen, K. Yang, D. Cai, and X. Hei. Document recommendation in social tagging services. In WWW, pages 391--400, 2010. Google ScholarDigital Library
- N. Hadaway. A narrow bridge to academic reading. Supporting English Language Learners, 66(7):38--41, 2009.Google Scholar
- M. Pera and Y.-K. Ng. Brek12: A book recommender for k-12 users. In ACM SIGIR, pages 1037--1038, 2012. Google ScholarDigital Library
- R. Qumsiyeh and Y.-K. Ng. Readaid: A robust and fully-automated readability assessment tool. In IEEE ICTAI, pages 539--546, 2011. Google ScholarDigital Library
- R. Slavin, C. Lake, B. Chambers, A. Cheung, and S. Davis. Effective reading programs for the elementary grades: A best-evidence synthesis. Review of Educational Research, 79(4):1391--1466, 2009.Google ScholarCross Ref
Index Terms
- Personalized recommendations on books for K-12 readers
Recommendations
Content-based book recommendations: Personalised and explainable recommendations without the cold-start problem
RecSys '21: Proceedings of the 15th ACM Conference on Recommender SystemsThe content-based book recommendation approach developed by Bookarang yields many improvements over existing systems, not only in recommendation quality and consistency, but also in flexibility, depth and transparency. Content-based book recommenders ...
What to read next?: making personalized book recommendations for K-12 users
RecSys '13: Proceedings of the 7th ACM conference on Recommender systemsFinding books that children/teenagers are interested in these days is a non-trivial task due to the diversity of topics covered in huge volumes of books with varied readability levels. Even though K-12 readers can turn to book recommenders to look for ...
BReK12: a book recommender for K-12 users
SIGIR '12: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrievalIdeally, students in K-12 grade levels can turn to book recommenders to locate books that match their interests. Existing book recommenders, however, fail to take into account the readability levels of their users, and hence their recommendations may be ...
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