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UPV at TREC Health Misinformation Track 2021 Ranking with SBERT and Quality Estimators (2112.06080v1)
Published 11 Dec 2021 in cs.IR and cs.AI
Abstract: Health misinformation on search engines is a significant problem that could negatively affect individuals or public health. To mitigate the problem, TREC organizes a health misinformation track. This paper presents our submissions to this track. We use a BM25 and a domain-specific semantic search engine for retrieving initial documents. Later, we examine a health news schema for quality assessment and apply it to re-rank documents. We merge the scores from the different components by using reciprocal rank fusion. Finally, we discuss the results and conclude with future works.
- Ipek Baris Schlicht (14 papers)
- Angel Felipe Magnossão de Paula (10 papers)
- Paolo Rosso (41 papers)