Smart Topic Miner shines at ISWC 2016

Last week I attended the 15th edition of the International Semantic Web Conference (ISWC 2016) where I presented our work on Smart Topic Miner (STM), the innovative application developed in collaboration with Springer Nature for automatically classifying research publications. STM was designed to classify proceedings and more in general any collection of articles by tagging them with relevant research areas and SN classification labels. It can be used for supporting editors in classifying new books and for quickly annotating several proceedings, thus creating a comprehensive knowledge base to assist the analysis of venues, journals and topic trends. Differently from other applications which characterize a text with topics, STM produce a full taxonomy of the relevant research areas rather than a flat list of keywords or categories. This helps editors and users to understand the context of each topic and its relationships with other research areas.

The demo of the system (available here was widely appreciated by the community and shortlisted for the best demo.

The papers presented at ISWC 2016 are the following:

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