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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Publication venues play an important role in the scholarly communication process. The number of publication venues has been increasing yearly, making it difficult for researchers to determine the most suitable venue for their publication. Most existing methods use citation count as the metric to measure the reputation of publication venues. However, this does not take into account the quality of citations. Therefore, it is vital to have a publication venue quality estimation mechanism. The ultimate goal of this research project is to develop a novel approach for ranking publication venues by considering publication history. The main aim of this research work is to propose a mechanism to identify the key Computer Science journals and conferences from various fields of research. Our approach is completely based on the citation network represented by publications. A modified version of the PageRank algorithm is used to compute the ranking scores for each publication. In our publication ranking method, there are many aspects that contribute to the importance of a publication, including the number of citations, the rating of the citing publications, the time metric and the authors’ reputation. Known publication venue scores have been formulated by using the scores of the publications. New publication venue ranking is taken care by the scores of Program Committee members which derive from their ranking scores as authors. Experimental results show that our publication ranking method reduces the bias against more recent publications, while also providing a more accurate way to determine publication quality.

Improving citation network scoring by incorporating author and program committee reputation