This tutorial will first explore the peculiarities of medical and health-related queries with respect to various facets (eg. vocabulary, users expertise, task) with the attempt of better understanding the underlying human intent. Second, as envisioned in semantic search, we will focus on the techniques and theoretical models that go beyond lexical matching to drive the search. We will cover both the symbolic semantics through the use of external resources (eg. UMLS, MeSH, Gene Ontology) and the distributional semantics relying on words collocations in the corpus including recent representation learning approaches of concepts and documents. Third, we will develop a roadmap on the main evaluation frameworks used in medical IR and then particularly examine and compare the effectiveness of semantic-based IR approaches. Finally, we summarize the research findings in the area and outline the key open research questions. To sum up, the goals of the tutorial are the following: 1. Summarize the lessons that can be drawn from studies investigating the peculiarities of medical-related information needs; 2. Present state-of-the art semantic search models supporting medical IRprocesses;3. Describe the major medical search evaluation benchmarks used in the IR community and report the key result trends achieved by the application of semantic IR models.
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