Framework for Hybrid Book Recommender System based on Opinion Mining
Anil Kumar1, Sonal Chawla2
1Anil Kumar*, Department of Computer Science, GGDSD College, Hariana, Hoshiarpur, Punjab, India.
2Dr. Sonal Chawla, Department of Computer Science and Applications, Panjab University, Chandigarh, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 914-919 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7518118419/2019©BEIESP | DOI: 10.35940/ijrte.D7518.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Recommender system plays an important role in automatic filtering out the important and personalized information for the intended user from a large amount of available information on internet. Recommender systems for books provide personalized recommendations to the readers for reading and to the librarians for book acquisition process. The objective of this research paper is four folds. Firstly, it conducts an extensive literature review pertaining to book recommender systems, secondly it specifies the popular recommendation techniques being used in specific application area of books, thirdly the paper reflects on the methodology followed and evaluation techniques being used based on the techniques discussed. Lastly, the paper proposes a framework for a book recommender system using best-suited recommendation techniques.
Keywords: Book Recommendation System, Hybrid Recommendation Technique, Recommendation System, Recommendation Techniques.
Scope of the Article: Data Mining Methods, Techniques, and Tools.