Abstract
In this paper, we present \(\mathsf {FairScholar}\), a novel scientific paper recommendation system that aims at balancing both relevance and diversity while searching for research papers in response to keyword queries. Our system performs a vertex reinforced random-walk, a time heterogeneous random-walk on the citation graph of papers in order to factor in diversity while serving recommendations. To incorporate semantically similar items in the search results, it uses a query expansion step that finds similar keywords using community detection. An online demo of our search engine is available at http://www.cnergres.iitkgp.ac.in/FairScholar/.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
References
Chakraborty, T., Modani, N., Narayanam, R., Nagar, S.: Discern: a diversified citation recommendation system for scientific queries. In: ICDE, pp. 555–566 (2015)
Huang, W., Wu, Z., Mitra, P., Giles, C.L.: RefSeer: a citation recommendation system. In: JCDL, London, United Kingdom, pp. 371–374 (2014)
Chakrabort, T., Sikdar, S., Tammana, V., Ganguly, N., Mukherjee, A.: Computer science fields as ground-truth communities: their impact, rise and fall. In: ASONAM 2013, Niagara, Ontario, Canada, pp. 426–433 (2013)
Witten, I.H., Paynter, G.W., Frank, E., Gutwin, C., Nevill-Manning, C.G.: Kea: practical automatic keyphrase extraction. In: JCDL. ACM, pp. 254–255 (1999)
Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. JSTAT 2008(10), P10008 (2008)
Mei, Q., Guo, J., Radev, D.: Divrank: the interplay of prestige and diversity in information networks. In: SIGKDD, New York, USA. ACM, pp. 1009–1018 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Anand, A., Chakraborty, T., Das, A. (2017). FairScholar: Balancing Relevance and Diversity for Scientific Paper Recommendation. In: Jose, J., et al. Advances in Information Retrieval. ECIR 2017. Lecture Notes in Computer Science(), vol 10193. Springer, Cham. https://doi.org/10.1007/978-3-319-56608-5_76
Download citation
DOI: https://doi.org/10.1007/978-3-319-56608-5_76
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56607-8
Online ISBN: 978-3-319-56608-5
eBook Packages: Computer ScienceComputer Science (R0)