Passage-level evidence in document retrieval

By Jamie Callan. 1994

Subfields: Information Retrieval & Search

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Citations in the corpus

Pretrained Transformers for Text Ranking: BERT and Beyond (2020, methodology): “, Callan [1994]. To add to the confusion, there are also examples where passages form the unit of retrieval, but passage scores are aggregated to rank documents, e.”
Quantitative evaluation of passage retrieval algorithms for question answering (2003, background): “Many passage retrieval techniques have been described in the context of improving document retrieval performance (e.g., [19, 1 ]), but we are not aware of any attempts to systematically study the performance of passage retrieval for question answering.”
UMass at TREC 2004: Novelty and HARD (2004, background): “Previous work has been inconclusive as to whether there is benefit to retrieving passages of different lengths [13, 3, 25].”
When will information retrieval be "good enough"? (2005, methodology): “Although our truth data used variable-length passages, fixed-length passage retrieval is at least as good as variablelength, and much easier to implement [8, 2, 12].”
Concept-Based Information Retrieval Using Explicit Semantic Analysis (2011, methodology): “Previous research using BOW representation has shown that breaking long documents into shorter passages can improve document retrieval [Callan 1994; Liu and Croft 2002], with the ranking of passages viewed as evidence to the relevance of their source documents.”
Relevance ranking for one to three term queries (1997, background): “…& Zobel, 1997; Knaus, Mittendorf, SchaÈ uble, & Sheridan, 1995), most passage retrieval methods divide a document into passages at the time it is added to the database (Allan, 1995; Callan, 1994; Hearst & Plaunt, 1993; Salton, Allan, & Buckley, 1993; Wilkinson, 1994; Wilkinson & Zobel, 1994; ).”
Is searching full text more effective than searching abstracts? (2009, background): “As a start, I have experimented with two different indexing granularities (full articles and spans), but alternative approaches include sliding windows [18,20], multi-para-graph segments [19], hierarchically-overlapping segments [38,39], and segments based on topic shifts [17].”
Modeling Diverse Relevance Patterns in Ad-hoc Retrieval (2018, methodology): “Callan [4] studied how passages can be defined,”
Long Document Ranking with Query-Directed Sparse Transformer (2020, methodology): “A vanilla strategy is to truncate or split the documents: Dai and Callan (2019) applied BERT ranking on each passage segmented from the document independently and explored different ways to combine the passage ranking scores, using the score of the first passage (BERT-FirstP), the best passage (BERT”
Information Retrieval: A Biomedical and Health Perspective (2020, result): “Similar findings were found in another analysis [182].”
Cross-Domain Modeling of Sentence-Level Evidence for Document Retrieval (2019, background): “This approach, in fact, is well motivated: There is a long thread of work in the information retrieval literature, dating back decades, that leverages passage retrieval techniques for document ranking (Hearst and Plaunt, 1993; Callan, 1994; Kaszkiel and Zo-bel, 1997; Clarke et al., 2000).”
GatfordCentre for Interactive Systems ResearchDepartment of Information (1996, result): “681 All runs BM25(2:0; 0:0;1;0:75) best passage weight and document weight (as reported also in [10]); the best results from this were similar to those in Table 1, but achieved with di erent parameters.”
Learning to model relatedness for news recommendation (2011, background): “Passage retrieval [7, 16, 21] can relax this problem to some degree.”
Leveraging Passage-level Cumulative Gain for Document Ranking (2020, methodology): “Callan [2] proposed that with the increase of documents’ length, it is natural to consider the fine-grained relevance, such as passage-level relevance, in ranking tasks.”
A Critique and Improvement of an Evaluation Metric for Text Segmentation (2002, background): “Text segmentation issues are also important for passage retrieval, a subproblem of information retrieval (Hearst and Plaunt, 1993; Salton, Allan, and Buckley, 1993; Callan, 1994; Kaszkiel and Zobel, 1997).”