Paper Info
Title
XML Retrieval by Improving Structural Relevance Measures Obtained from Summary Models
Abstract
In XML retrieval, there is often more than one element in the same document that could represent the same focused result. So, a key challenge for XML retrieval systems is to return the set of elements that best satisfies the information need of the end-user in terms of both content and structure. At INEX, there have been numerous proposals for how to incorporate structural constraints and hints into ranking. These proposals either boost the score of or filter out elements that have desirable structural properties. An alternative approach that has not been explored is to rank elements by improving their structural relevance. Structural relevance is the expected relevance of a list of elements, based on a graphical model of how users browse elements within documents. In our approach, we use summary graphs to describe the process of a user browsing from one part of a document to another.In this paper, we develop an algorithm to structurally score retrieval scenarios using structural relevance. The XML retrieval system identifies the candidate scenarios. We apply structural relevance with a given summary model to identify the most structurally relevant scenario. This results in improved system performance. Our approach provides a consistent way to apply different user models to ranking. We also explore the use of score boosting using these models.
Year
DOI
Venue
2007
10.1007/978-3-540-85902-4_3
INEX
Keywords
DocType
Volume
different user model,xml retrieval,graphical model,desirable structural property,summary models,structural relevance,structural constraint,expected relevance,alternative approach,retrieval scenario,improving structural relevance measures,xml retrieval system
Conference
4862
ISSN
Citations 
PageRank 
0302-9743
2
0.37
References 
Authors
8
3
Name
Order
Citations
PageRank
mir sadek ali120.37
Mariano P. Consens21203387.78
Shahan Khatchadourian31028.57