Publication Type:

Journal Article

Source:

Lecture Notes in Computational Vision and Biomechanics, Springer Netherlands, Volume 28, p.437-446 (2018)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042412210&doi=10.1007%2f978-3-319-71767-8_36&partnerID=40&md5=c03971e32aa5aaaa2c8d7e1802a12b97

Abstract:

<p>Personalization is an emerging topic in the field of Research paper recommender systems and academic research. It is a technique to creative and efficient user profiles to achieve improved recommendations. Our work proposes a new user model to understand user behavior for personalization. This model initially extracts keywords based on the online behaviour of the user. The subsequent steps include concept extraction and user profile ontology construction to derive inferences and define relationships. The suggested model clearly depicts hierarchical ordering of the user’s long-term and current research interests. Furthermore, the adoption of our model contributes to improvement of recommendations. © 2018, Springer International Publishing AG.</p>

Notes:

cited By 0

Cite this Research Publication

T. Sripadh and Ramesh, G., “Personalized research paper recommender system”, Lecture Notes in Computational Vision and Biomechanics, vol. 28, pp. 437-446, 2018.

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