Relevance: A review of the literature and a framework for thinking on the notion in information science. Part III: Behavior and effects of relevance

By Tefko Saracevic. J. Assoc. Inf. Sci. Technol., 2007

314 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/66725553dcb3179097c6c75b7a5e3e1863d12588

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jun Xu
2. Hang Li
3. Diane Kelly
4. Daniel E. Rose
5. Jimmy J. Lin
6. Tie-Yan Liu
7. Jiafeng Guo
8. Olivier Chapelle

In Information Systems

1. Jun Xu
2. Hang Li
3. Diane Kelly
4. Daniel E. Rose
5. Tie-Yan Liu
6. Olivier Chapelle
7. Jimmy J. Lin
8. Allison Chang

In Management Science and Operations Research

1. Diane Kelly
2. Jun Xu
3. Hang Li

Citations in the corpus

• Semantic Matching in Search (2014, background): “Among them, relevance [156, 171, 157] is the most important factor, which is also the focus of this survey.”
• Methods for Evaluating Interactive Information Retrieval Systems with Users (2009, background): “We know from studies that have attempted to define relevance that there are many interpretations of this term, as well as many manifestations [235, 236].”
• Expected reciprocal rank for graded relevance (2009, unknown): “…as the query), that judgments are binary (relevant / not relevant), independent (relevance of document A does not depend on relevance of document B), stable (judgments do not change over time), consistent (judgments are consistent across editors), and complete (there are no missing judgments) [23].”
• To personalize or not to personalize: modeling queries with variation in user intent (2008, unknown): “Relevance is a complex concept and a review of that work is beyond the scope of this paper (see [18] for a review).”
• Crowdsourcing for relevance evaluation (2008, background): “For these reasons, many researchers in both industry and academia now rely on the strategy of using editorial resources to create their own new relevance assessments from scratch, specific to the needs of the system they are testing.”
• Standards for the preparation and writing of Psychology review articles (2009, unknown): “El objetivo es, e n un primer momento, hallar, identificar, seleccionar y obtener informacion pert inente y relevante ( Saracevic, 2007a, 2007b ) (C-2).”
• Relevance: A review of the literature and a framework for thinking on the notion in information science. Part II: nature and manifestations of relevance (2007, unknown): “Building on the examination of relevance in the preceding (1975) review, this work (2007) updates the travails of relevance in information science for the past 30 years or so.”
• Information Retrieval Evaluation (2011, unknown): “Saracevic [154] then described various user studies that had been done to examine each of these assumptions.”