Journal
IEEE ACCESS
Volume 10, Issue -, Pages 106886-106896Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3212531
Keywords
Social networking (online); Recommender systems; Collaboration; Clustering algorithms; Information retrieval; Internet; Clustering methods; Publishing; Information analysis; Clustering; information retrieval; profiling; publication venue recommendation; recommender systems
Categories
Funding
- Spanish Agencia Estatal de Investigacion'' [PID2019-106758GB-C31]
- Spanish FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades'' [A-TIC-146-UGR20]
- European Regional Development Fund (ERDF-FEDER)
Ask authors/readers for more resources
This paper studies the problem of venue recommendation and proposes a method that combines clustering techniques and information retrieval to construct topic-based profiles, as well as utilizes authorship information to improve the recommendations.
In this paper, we study the venue recommendation problem in order to help researchers identify a journal or conference to submit a given paper. A common approach for tackling this problem is to build profiles to define the scope of each venue. These profiles are then compared against the target paper. In our approach, we will study how clustering techniques can be used to construct topic-based profiles and an information retrieval-based approach be used to obtain the final recommendations. Additionally, we will explore how the use of authorship (which supplements the information) helps to improve the recommendations.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
