期刊
IEEE ACCESS
卷 10, 期 -, 页码 106886-106896出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3212531
关键词
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
资金
- 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)
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.
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