2011
DOI: 10.1007/978-3-642-23708-9_4
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Search Snippet Evaluation at Yandex: Lessons Learned and Future Directions

Abstract: This papers surveys different approaches to evaluation of web search summaries and describes experiments conducted at Yandex. We hypothesize that the complex task of snippet evaluation is best solved with a range of different methods. Automation of evaluation based on available manual assessments and clickthrough analysis is a promising direction.

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Cited by 21 publications
(13 citation statements)
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“…These results indicate that the participants spent relatively less effort in evaluating the search results in the controversial topic task while addressing more attention to the actual selected webpages. The viewing and result selection patterns were in line with what was reported by previous studies (Balatsoukas & Ruthven, ; Höchstötter & Lewandowski, ; Pan et al, ; Savenkov, Braslavski, & Lebedev, ): The top search results were viewed and selected more often than the ones at the bottom of the SERPs. In addition, the participants verbalized especially the formulation of the search query and did not verbalize thoughts on the evaluation of search result very often.…”
Section: Discussionsupporting
confidence: 89%
“…These results indicate that the participants spent relatively less effort in evaluating the search results in the controversial topic task while addressing more attention to the actual selected webpages. The viewing and result selection patterns were in line with what was reported by previous studies (Balatsoukas & Ruthven, ; Höchstötter & Lewandowski, ; Pan et al, ; Savenkov, Braslavski, & Lebedev, ): The top search results were viewed and selected more often than the ones at the bottom of the SERPs. In addition, the participants verbalized especially the formulation of the search query and did not verbalize thoughts on the evaluation of search result very often.…”
Section: Discussionsupporting
confidence: 89%
“…Recent work has examined the generation of snippets from more complex angles -from manipulating underlying indexes [4,49] to language modelling [14,32], as well as using user search data to improve the generation process [1,42]. Previous generation approaches also may not consider what parts of a document searchers actually nd useful.…”
Section: Generating Snippet Textmentioning
confidence: 99%
“…With respect to the effect of domain knowledge on eye gaze, it was found that users with a high level of domain knowledge are less likely to attend to the element of title, as demonstrated by this study's undergraduate and postgraduate biology users with a high level of biology knowledge. However, a previous finding has suggested that titles of lower ranked items receive more attention than the snippets of higher ranked items (Savenkov et al, 2011), and the title and abstract of SERPs receive more attention than other elements by general public users (Wang et al, 2015). As such, this study has provided evidence that a user's level of domain knowledge affects eye gaze behaviour.…”
Section: Areas Of Interestmentioning
confidence: 56%
“…In Web search environments, users paid more attention to the top three, next top three and top advertisements than other regions, such as related searches on search engine results page (SERP) (Dumais et al, 2010), while few abstracts in SERPs from Google and Yahoo were viewed in query reformulation (Lorigo et al, 2008). However, the title of lower ranked items was considered more important than the snippets of higher ranked items (Savenkov, Braslavski, & Lebedev, 2011). Wang, Xie, and Lee's (2015) study found that the title and abstract of SERPs were ranked the top two elements in terms of total fixation time and fixation count.…”
Section: Eye Gaze and Search Interface Designmentioning
confidence: 99%