Redundant documents and search effectiveness

By Yaniv Bernstein, Justin Zobel. 2005

77 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Safety Research

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Citations in the corpus

Pretrained Transformers for Text Ranking: BERT and Beyond (2020, neutral): “s essentially the same article was retrieved more than once and thus entered the judgment pool multiple times. While researchers have previously studied the impact of near-duplicate documents, e.g., [Bernstein and Zobel, 2005, Fröbe et al., 2020], a thorough analysis has not been applied to TREC-COV”
Clustered Sequence Representation for Fast Homology Search (2007, unknown): “Using SPEX can yield signiﬁcant savings over selecting every chunk without any degradation in the quality of results (Bernstein and Zobel, 2004, 2005).”
Novelty and diversity in information retrieval evaluation (2008, background): “Bernstein and Zobel [5] examined the impact of nearduplicates on the TREC GOV2 collection.”
Information Retrieval Evaluation (2011, background): “The current judgments could be used as the starting point for other types of relevance judgments, such as removal of “duplicate” documents [24], or the use of graded relevance judgments [99, 162] or even the measurement of some type of learning effect (the TREC novelty track).”
The Effect of Content-Equivalent Near-Duplicates on the Evaluation of Search Engines (2020, methodology): “…engine has not been overlooked: Treating results as irrelevant when they are found to be content-equivalent to a document the user has already seen, Bernstein and Zobel [4] applied this so-called “novelty principle” during their analysis of content-equivalent documents within the GOV collections.”