Relevance Clues

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 results so far include a user model for relevance assessments in academic search systems taking into account popularity data, e.g., citation or download frequencies of the particular work. The model aims at a systematic representation of elements of a search result as potential relevance clues, subjective relevance criteria users apply when assessing the results, and contextual relevance factors as variables influencing relevance judgments. Furthermore, a methodological framework for incorporating popularity data in experimental studies on relevance criteria has been developed.

Publications

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. https://doi.org/10.1145/3295750.3298978

Behnert, C. (2019). Kriterien und Einflussfaktoren bei der Relevanzbewertung von Surrogaten in akademischen Informationssystemen. In: Information – Wissenschaft & Praxis 70 (1), 24-32. https://doi.org/10.1515/iwp-2019-0002

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.

Project team

Christiane Behnert (doctoral student)
Ulrike Spree (supervisor)