FREME: Multilingual Semantic Enrichment with Linked Data and Language Technologies

Milan Dojchinovski; Felix Sasaki; Tatjana Gornostaja; Sebastian Hellmann; Erik Mannens; Frank Salliau; Michele Osella; Phil Ritchie; Giannis Stoitsis; Kevin Koidl; Markus Ackermann; Nilesh Chakraborty

In: Proceedings of LREC 2016. International Conference on Language Resources and Evaluation (LREC-2016), May 23-28, Portoro¸, Slovenia, 2016.


In the recent years, Linked Data and Language Technology solutions gained popularity. Nevertheless, their coupling in real-world business is limited due to several issues. Existing products and services are developed for a particular domain, can be used only in combination with already integrated datasets or their language coverage is limited. In this paper, we present an innovative solution FREME - an open framework of e-Services for multilingual and semantic enrichment of digital content. The framework integrates six interoperable e-Services. We describe the core features of each e-Service and illustrate their usage in the context of four business cases: i) authoring and publishing; ii) translation and localisation; iii) cross-lingual access to data; and iv) personalised Web content recommendations. Business cases drive the design and development of the framework.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence