A probabilistic model to exploit user expectations in XML information retrieval
作者：
Highlights：
• XML information retrieval models return nested elements as result to a user query.
• User explores only elements that he expects to be relevant.
• The elements structural characteristics (tag, position…) attract the user attention.
• Important elements must be boosted according to their structural context.
• Element importance as prior probability improves retrieval effectiveness.
摘要
•XML information retrieval models return nested elements as result to a user query.•User explores only elements that he expects to be relevant.•The elements structural characteristics (tag, position…) attract the user attention.•Important elements must be boosted according to their structural context.•Element importance as prior probability improves retrieval effectiveness.
论文关键词：Priors,Element importance,User browsing map,Language model
论文评审过程：Received 26 July 2014, Revised 26 May 2016, Accepted 27 June 2016, Available online 5 July 2016, Version of Record 23 November 2016.
论文官网地址：https://doi.org/10.1016/j.ipm.2016.06.008
