Title
Improving search result summaries by using searcher behavior data
Abstract
Query-biased search result summaries, or "snippets", help users decide whether a result is relevant for their information need, and have become increasingly important for helping searchers with difficult or ambiguous search tasks. Previously published snippet generation algorithms have been primarily based on selecting document fragments most similar to the query, which does not take into account which parts of the document the searchers actually found useful. We present a new approach to improving result summaries by incorporating post-click searcher behavior data, such as mouse cursor movements and scrolling over the result documents. To achieve this aim, we develop a method for collecting behavioral data with precise association between searcher intent, document examination behavior, and the corresponding document fragments. In turn, this allows us to incorporate page examination behavior signals into a novel Behavior-Biased Snippet generation system (BeBS). By mining searcher examination data, BeBS infers document fragments of most interest to users, and combines this evidence with text-based features to select the most promising fragments for inclusion in the result summary. Our extensive experiments and analysis demonstrate that our method improves the quality of result summaries compared to existing state-of-the-art methods. We believe that this work opens a new direction for improving search result presentation, and we make available the code and the search behavior data used in this study to encourage further research in this area.
Year
DOI
Venue
2013
10.1145/2484028.2484093
SIGIR
Keywords
Field
DocType
searcher behavior data,behavioral data,search result presentation,bebs infers document fragment,mining searcher examination data,corresponding document fragment,result document,query-biased search result summary,improving search result summary,ambiguous search task,document examination behavior,result summary
Data mining,Information needs,Information retrieval,Computer science,Pointer (user interface),Behavioral data,Scrolling,Snippet
Conference
Citations 
PageRank 
References 
16
0.65
31
Authors
3
Name
Order
Citations
PageRank
Mikhail S. Ageev11295.05
Dmitry Lagun235114.96
Eugene Agichtein34549269.70