Knowledge bases (KB's) contribute to advances in semantic search, Web analytics, and smart recommendations. Their coverage of domain-specific knowledge is limited, though. This demo presents the KnowLife portal, a large KB for health and life sciences, automatically constructed from Web sources. Prior work on biomedical ontologies has focused on molecular biology: genes, proteins, and pathways. In contrast, KnowLife is a one-stop portal for a much wider range of relations about diseases, symptoms, causes, risk factors, drugs, side effects, and more. Moreover, while most prior work relies on manually curated sources as input, the KnowLife system taps into scientific literature as well as online communities. KnowLife uses advanced information extraction methods to populate the relations in the KB. This way, it learns patterns for relations, which are in turn used to semantically annotate newly seen documents, thus aiding users in “speed-reading”. We demonstrate the value of the KnowLife KB by various use-cases, supporting both layman and professional users.
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