What Snippets Say About Pages in Federated Web Search
by Thomas Demeester, Dong Nguyen, Dolf Trieschnigg, Chris Develder, and Djoerd Hiemstra
What is the likelihood that a Web page is considered relevant to a query, given the relevance assessment of the corresponding snippet? Using a new federated IR test collection that contains search results from over a hundred search engines on the internet, we are able to investigate such research questions from a global perspective. Our test collection covers the main Web search engines like Google, Yahoo!, and Bing, as well as a number of smaller search engines dedicated to multimedia, shopping, etc., and as such reflects a realistic Web environment. Using a large set of relevance assessments, we are able to investigate the connection between snippet quality and page relevance. The dataset is strongly inhomogeneous, and although the assessors’ consistency is shown to be satisfying, care is required when comparing resources. To this end, a number of probabilistic quantities, based on snippet and page relevance, are introduced and evaluated.
The paper will be presented at the Asia Information Retrieval Societies Conference AIRS 2012 in Tianjin, China