<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>9017</REFNUM><AUTHORS><AUTHOR>Ali,S.</AUTHOR><AUTHOR>Consens,M.</AUTHOR><AUTHOR>Kazai,G.</AUTHOR><AUTHOR>Lalmas,M.</AUTHOR></AUTHORS><YEAR>2008</YEAR><TITLE>Structural Relevance: A Common Basis for the Evaluation of Structured Document Retrieval</TITLE><PLACE_PUBLISHED>17th ACM Conference on Information and Knowledge Management (CIKM 2008), Napa Valley</PLACE_PUBLISHED><PUBLISHER>ACM Press</PUBLISHER><PAGES>1153-1162</PAGES><LABEL>Ali:2008:9017</LABEL><KEYWORDS><KEYWORD>Strucutural Relevance</KEYWORD></KEYWORDS<ABSTRACT>This paper presents a uni?ed framework for the evaluation of a range of structured document retrieval (SDR) approaches and tasks. The framework is based on a model of tree re- trieval, evaluated using a novel extension of the Structural Relevance (SR) measure. The measure replaces the assump- tion of independence in traditional information retrieval (IR) with a notion of redundancy that takes into account the user navigation inside documents while seeking relevant informa- tion. Unlike existing metrics for SDR, our proposed frame- work does not require the computation of an ideal ranking which has, thus far, prevented the practical application of such measures. Instead, SR builds on a Markovian model of user navigation that can be estimated through the use of structural summaries. The results of this paper (supported by experimental validation using INEX data) show that SR de?ned over a tree retrieval model can provide a common basis for the evaluation of SDR approaches across various structured search tasks.</ABSTRACT></RECORD></RECORDS></XML>