TY - GEN
T1 - A Hybrid Approach for the Recommendation of Scholarly Journals
AU - Abbasi, Iqra Iftikhar
AU - Abbas, Muhammad Azeem
AU - Hammad, Shiza
AU - Jilani, Muhammad Taha
AU - Ahmed, Shabbir
AU - Nisa, Saba Un
PY - 2020/4/30
Y1 - 2020/4/30
N2 - The increasing number of scholarly journals have made it difficult for authors to select the most suitable journal that publishes their research. Existing search systems that recommend journals for manuscript submission are either based on author 's profile, bibliographic data or the copublication network. These approaches are not useful for beginner researchers who have no publication records or for those who are interested in new research domains. The present work proposes a hybrid approach that combines clustering and document similarity for the recommendation of scholarly venues. The proposal was evaluated both objectively and subjectively using domain experts. The results of mean average precision (0.84) and normalized discounted cumulative gain (0.89) shows positive recommendations made by the proposed approach.
AB - The increasing number of scholarly journals have made it difficult for authors to select the most suitable journal that publishes their research. Existing search systems that recommend journals for manuscript submission are either based on author 's profile, bibliographic data or the copublication network. These approaches are not useful for beginner researchers who have no publication records or for those who are interested in new research domains. The present work proposes a hybrid approach that combines clustering and document similarity for the recommendation of scholarly venues. The proposal was evaluated both objectively and subjectively using domain experts. The results of mean average precision (0.84) and normalized discounted cumulative gain (0.89) shows positive recommendations made by the proposed approach.
KW - Clustering.
KW - Journal recommendations
KW - Recommendation system
UR - https://ieeexplore.ieee.org/document/9080032
UR - http://www.scopus.com/inward/record.url?scp=85084957398&partnerID=8YFLogxK
U2 - 10.1109/ICISCT49550.2020.9080032
DO - 10.1109/ICISCT49550.2020.9080032
M3 - Conference publication
AN - SCOPUS:85084957398
T3 - ICISCT 2020 - 2nd International Conference on Information Science and Communication Technology
BT - 2020 International Conference on Information Science and Communication Technology (ICISCT)
PB - IEEE
T2 - 2nd International Conference on Information Science and Communication Technology, ICISCT 2020
Y2 - 8 February 2020 through 9 February 2020
ER -