most citedClustering articles based on semantic similarity

74 citations · 136 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DL201722 cited

Contextualization of topics: Browsing through the universe of bibliographic information

Rob Koopman, Shenghui Wang, Andrea Scharnhorst

This paper describes how semantic indexing can help to generate a contextual overview of topics and visually compare clusters of articles. The method was originally developed for a…

cs.IR201724 cited

Mutual Information based labelling and comparing clusters

Rob Koopman, Shenghui Wang

After a clustering solution is generated automatically, labelling these clusters becomes important to help understanding the results. In this paper, we propose to use a Mutual Info…

cs.DL201774 cited

Clustering articles based on semantic similarity

Shenghui Wang, Rob Koopman

Document clustering is generally the first step for topic identification. Since many clustering methods operate on the similarities between documents, it is important to build repr…

cs.DL20155 cited

Contextualization of topics - browsing through terms, authors, journals and cluster allocations

Rob Koopman, Shenghui Wang, Andrea Scharnhorst

This paper builds on an innovative Information Retrieval tool, Ariadne. The tool has been developed as an interactive network visualization and browsing tool for large-scale biblio…

cs.DL201511 cited

Ariadne's Thread - Interactive Navigation in a World of Networked Information

Rob Koopman, Shenghui Wang, Andrea Scharnhorst +1

This work-in-progress paper introduces an interface for the interactive visual exploration of the context of queries using the ArticleFirst database, a product of OCLC. We describe…