Edit Entity: TWC Talk - SHER: A Scalable Highly Expressive Reasoner and its applications

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Comment:	An impediment to the realization of the semantic web vision has been the inability of semantic web systems to successfully scale to large and expressive knowledge bases. In this talk, we will present advances in scaling ontology reasoning made over the past three years at IBM Research. We will also discuss three concrete applications of scalable ontology reasoning that illustrate its value and potential to transform how information is integrated, analyzed and exchanged. The first application showcases the use of ontology reasoning to automate common labor intensive and error prone clinical tasks, such as cohort selection of patients for clinical trials, infectious disease monitoring, and clinical decision support. An obstacle to automating these tasks is the need to bridge the semantic gap between raw patient data, such as laboratory tests, and the way clinicians interpret this data. The second demonstrates how ontologies can be effectively used to cleanse the output of text analytics over large text corpora. Finally, the last application shows how SHER technology enables efficient semantic search over biomedical literature.
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