UPV at TREC Health Misinformation Track 2021 Ranking with SBERT and Quality Estimators
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 8 of its 21 references that are in the map. First posted on arXiv 11 Dec 2021.
Builds on
8 of 21 references.
References · 8
- 2017Attention Is All You Needcited by 59,932
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
- 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
- 2017Evaluation Measures for Relevance and Credibility in Ranked Listscited by 6
- 2020Automatically Assessing Quality of Online Health Articlescited by 2
- 2021University of Copenhagen Participation in TREC Health Misinformation Track 2020cited by 2
Built on by
Citing papers per year: 2023: 2.
2 papers.