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Characterising Concepts of Interest Leveraging Linked Data and the Social Web.

, , , and . Web Intelligence, page 519-526. IEEE Computer Society, (2013)

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Are We Really Standing on the Shoulders of Giants?, and . NoISE@ESWC, volume 1435 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)Improving Natural Language Inference Using External Knowledge in the Science Questions Domain., , , , , , , , , and 1 other author(s). AAAI, page 7208-7215. AAAI Press, (2019)Hierarchical interest graph from tweets., , , and . WWW (Companion Volume), page 311-312. ACM, (2014)A Measure for Dialog Complexity and its Application in Streamlining Service Operations., , and . CoRR, (2017)Answering Science Exam Questions Using Query Rewriting with Background Knowledge., , , , , , , , and . CoRR, (2018)An Interface for Annotating Science Questions., , , , , , , , , and 3 other author(s). EMNLP (Demonstration), page 102-107. Association for Computational Linguistics, (2018)Twitris: A System for Collective Social Intelligence., , , , , , and . Encyclopedia of Social Network Analysis and Mining, (2014)Twitris: A System for Collective Social Intelligence., , , , , , , and . Encyclopedia of Social Network Analysis and Mining. 2nd Ed., Springer, (2018)Knowledge Enabled Approach to Predict the Location of Twitter Users., , , and . ESWC, volume 9088 of Lecture Notes in Computer Science, page 187-201. Springer, (2015)Domain-specific hierarchical subgraph extraction: A recommendation use case., , , and . BigData, page 666-675. IEEE Computer Society, (2017)