publication . Preprint . 2015

The Anatomy of Relevance: Topical, Snippet and Perceived Relevance in Search Result Evaluation

Chuklin, Aleksandr; de Rijke, Maarten;
Open Access English
  • Published: 26 Jan 2015
Currently, the quality of a search engine is often determined using so-called topical relevance, i.e., the match between the user intent (expressed as a query) and the content of the document. In this work we want to draw attention to two aspects of retrieval system performance affected by the presentation of results: result attractiveness ("perceived relevance") and immediate usefulness of the snippets ("snippet relevance"). Perceived relevance may influence discoverability of good topical documents and seemingly better rankings may in fact be less useful to the user if good-looking snippets lead to irrelevant documents or vice-versa. And result items on a search engine result page (SERP) with high snippet relevance may add towards the total utility gained by the user even without the need to click those items. We start by motivating the need to collect different aspects of relevance (topical, perceived and snippet relevances) and how these aspects can improve evaluation measures. We then discuss possible ways to collect these relevance aspects using crowdsourcing and the challenges arising from that.
Comment: SIGIR 2014 Workshop on Gathering Efficient Assessments of Relevance
free text keywords: Computer Science - Information Retrieval, H.3.3
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Funded by
NWO| Semantic Search in E-Discovery
  • Funder: Netherlands Organisation for Scientific Research (NWO) (NWO)
  • Project Code: 2300168486
Virtual Centre of Excellence for Research in Violent Online Political Extremism
  • Funder: European Commission (EC)
  • Project Code: 312827
  • Funding stream: FP7 | SP1 | SEC
NWO| SPuDisc: Searching Public Discourse
  • Funder: Netherlands Organisation for Scientific Research (NWO) (NWO)
  • Project Code: 2300176811
NWO| Modeling and Learning from Implicit Feedback in Information Retrieval
  • Funder: Netherlands Organisation for Scientific Research (NWO) (NWO)
  • Project Code: 2300171779
Linguistically Motivated Semantic aggregatIon engiNes
  • Funder: European Commission (EC)
  • Project Code: 288024
  • Funding stream: FP7 | SP1 | ICT
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