MacEwan University at the TREC 2020 Fair Ranking Track
information retrieval, rank aggregation
The MacEwan University School of Business submitted two runs for the TREC 2020 Fair Ranking Track. For this task, we indexed the document abstracts and the associated metadata from the provided Semantic Scholar dataset into a single Solr1 node using a standard Tokenizer chain. For each of the evaluation queries, we executed a query for each of the documents that required reranking. For each query-document pairing, we collected the BM25 similarity score for the “paperAbstract” and “title” fields. Each of the documents are ranked for each field based on the similarity score with the query text, with ties sharing their combined rank. This resulted in two ranked lists for each query.
Almquist, B. MacEwan University at the 2020 TREC Fair Ranking Track. Proceedings of the 29th Text REtrieval Conference, 2020. https://trec.nist.gov/pubs/trec29/trec2020.html
Presented on November 16-20, 2020, at the "Twenty-Ninth Text REtrieval Conference (TREC 2020)” held online.
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