This dataset consists of 7762 publications (Abstract and Title) in computer science from DBLP between 2013-2019 (AAAI, ACM SIGMOD, ACM SIGIR, ACM SIGKDD, ICCCN, ICSE, WWW, and ISWC).
@Article{Jelodar2020, journal="Soft Computing", issn="1432-7643", volume="24", year="2020", title="Recommendation System based on Semantic Scholar Mining and Topic modeling on Conferences publications ", abstract="Recommendation systems are of great assistance to online users in the internet society. Today, these systems are highly used in computer science in various aspects of the Internet portals such as social networks and library websites. There are several approaches to implement recommendation systems. Latent Dirichlet Allocation (LDA) is one of the popular techniques in Topic Modeling. Recently, researchers have proposed many approaches based on recommendation Systems and LDA. Regarding the importance of the subject, in this paper, we discover the trends of the topics and find a relationship between LDA topics and Scholar-Context-documents. We apply probabilistic topic modeling based on Gibbs sampling algorithms for semantic mining from eight conference publications in computer science from the DBLP dataset. Based on the obtained experimental results, our semantic framework can be effective to help organizations to better organize these conferences and cover future research topics.", author="Jelodar, Hamed and et al", pages="1--30"}