TY - GEN
T1 - Incorporating full text and bibliographic features to improve scholarly journal recommendation
AU - Ghosal, Tirthankar
AU - Chakraborty, Ananya
AU - Sonam, Ravi
AU - Ekbal, Asif
AU - Saha, Sriparna
AU - Bhattacharyya, Pushpak
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - Selecting an appropriate venue to communicate one's research is the very first step in scholarly communication. Many papers are simply rejected from the editor's desk on not being submitted to the right journal. Existing journal recommender systems extract keywords only from the title and abstract sections of candidate articles and produce journal recommendations based on their weighted-match with a domain-specific vocabulary. Here in this work, we investigate a simple yet effective approach by incorporating additional information from bibliography and body section of academic manuscripts and show their potency to yield a better recommendation. On a closed set of ten different journals, our content-based recommender achieves significant improvement over the usual baselines (at least ~ 10%). Our preliminary approach is simple yet promising and if suitably applied could efficiently recommend journals from a larger pool as well.
AB - Selecting an appropriate venue to communicate one's research is the very first step in scholarly communication. Many papers are simply rejected from the editor's desk on not being submitted to the right journal. Existing journal recommender systems extract keywords only from the title and abstract sections of candidate articles and produce journal recommendations based on their weighted-match with a domain-specific vocabulary. Here in this work, we investigate a simple yet effective approach by incorporating additional information from bibliography and body section of academic manuscripts and show their potency to yield a better recommendation. On a closed set of ten different journals, our content-based recommender achieves significant improvement over the usual baselines (at least ~ 10%). Our preliminary approach is simple yet promising and if suitably applied could efficiently recommend journals from a larger pool as well.
KW - Full text processing
KW - Journal recommendation
KW - Scholarly communications
UR - http://www.scopus.com/inward/record.url?scp=85071012269&partnerID=8YFLogxK
U2 - 10.1109/JCDL.2019.00077
DO - 10.1109/JCDL.2019.00077
M3 - Conference contribution
AN - SCOPUS:85071012269
T3 - Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
SP - 374
EP - 375
BT - Proceedings - 2019 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019
A2 - Bonn, Maria
A2 - Wu, Dan
A2 - Downie, Stephen J.
A2 - Martaus, Alain
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2019
Y2 - 2 June 2019 through 6 June 2019
ER -