English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Recommendation systems have an important place to help online users in theinternet society. Recommendation Systems in computer science are of verypractical use these days in various aspects of the Internet portals, such associal networks, and library websites. There are several approaches toimplement recommendation systems, Latent Dirichlet Allocation (LDA) is one thepopular techniques in Topic Modeling. Recently, researchers have proposed manyapproaches based on Recommendation Systems and LDA. According to importance ofthe subject, in this paper we discover the trends of the topics and findrelationship between LDA topics and Scholar-Context-documents. In fact, Weapply probabilistic topic modeling based on Gibbs sampling algorithms for asemantic mining from six conference publications in computer science from DBLPdataset. According to our experimental results, our semantic framework can beeffective to help organizations to better organize these conferences and coverfuture research topics.

Recommendation System based on Semantic Scholar Mining and Topic modeling: A behavioral analysis of researchers from six conferences