OSIBR: Ontology Focused Semantic Intelligence Approach for Book Recommendation
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-01942-5_40
Reference20 articles.
1. Darekar, R., Dayma, K., Parabh, R., Kurhade, S.: A hybrid model for book recommendation. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 120–124, April 2018
2. Tsuji, K., Yoshikane, F., Sato, S., Itsumura, H.: Book recommendation using machine learning methods based on library loan records and bibliographic information. In: 2014 IIAI 3rd International Conference on Advanced Applied Informatics, pp. 76–79. IEEE, August 2014
3. Mclean, N., Davis, J.: Utilizing semantically rich big data to enhance book recommendation engines. In: 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pp. 1434–1441. IEEE, December 2016
4. Vishal, K., Deepak, G., Santhanavijayan, A.: An approach for retrieval of text documents by hybridizing structural topic modelling and pointwise mutual information. In: Innovations in Electrical and Electronic Engineering, pp. 969–977. Springer, Singapore (2021)
5. Sabitha, S., Choudhury, T.: Proposed approach for book recommendation based on user k-NN. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds.) Advances in Computer and Computational Sciences. AISC, vol. 554, pp. 543–558. Springer, Singapore (2018). Doi: https://doi.org/10.1007/978-981-10-3773-3_53
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