Despite the abundance of biomedical literature and health discussions in online communities, it is often tedious to retrieve informative contents for health-centric information needs. Users can query scholarly work in PubMed by keywords and MeSH terms, and resort to Google for everything else. This demo paper presents the DeepLife system, to overcome the limitations of existing search engines for life science and health topics. DeepLife integrates large knowledge bases and harnesses entity linking methods, to support search and exploration of scientific literature, newspaper feeds, and social media, in terms of keywords and phrases, biomedical entities, and taxonomic categories. It also provides functionality for entityaware text analytics over health-centric contents.
CITATION STYLE
Ernst, P., Siu, A., Milchevski, D., Hoffart, J., & Weikum, G. (2016). DeepLife: An entity-aware search, analytics and exploration platform for health and life sciences. In 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - System Demonstrations (pp. 19–24). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p16-4004
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