Relevance Clues: Development and empirical examination of a model for relevance decisions on search results based on individual user criteria
In today’s knowledge-based society, people regularly search for information in digital information systems. They decide whether a search result is helpful to solve their search task or not based on diverse and highly subjective criteria. The purpose of this research project is to determine subjective criteria as well as the interdependence between different criteria on individual relevance decisions regarding search results in an academic context. Dependable results will be achieved by applying an experimental research design involving human test persons – an approach still rarely used in Information Science – and by building a sample large enough for statistically firm statements.
Project period: August 2016 – July 2019
Funding: Ph.D. scholarship at the Hamburg University of Applied Sciences (HAW Hamburg)
Behnert, C. (2019). Investigating the Effects of Popularity Data on Predictive Relevance Judgments in Academic Search Systems. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval – CHIIR ’19 (S. 437–440). New York, New York, USA: ACM Press.
Behnert, C. (2019). Kriterien und Einflussfaktoren bei der Relevanzbewertung von Surrogaten in akademischen Informationssystemen. In: Information – Wissenschaft & Praxis 70 (1), 24-32.
Behnert, C. (2017). Relevance Clues – Developing an Experimental Design to Examine the Criteria Behind Relevance Judgments. In M. Gäde, V. Trkulja, & V. Petras (Hrsg.), Everything Changes, Everything Stays the Same? Understanding Information Spaces. Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin, 13th—15th March 2017. Glückstadt: Verlag Werner Hülsbusch.