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Abstract

We present a theoretical framework to evaluate XML retrieval. XML retrieval deals with retrieving those document components-the XML elements-that specifically answer a query. In this article, theoretical evaluation is concerned with the formal representation of qualitative properties of retrieval models. It complements experimental methods by showing the properties of the underlying reasoning assumptions that decide when a document is about a query. We define a theoretical methodology based on the idea of "aboutness" and apply it to current XML retrieval models. This allows comparing and analyzing the reasoning behavior of XML retrieval models experimented within the INEX evaluation campaigns. For each model we derive functional and qualitative properties that qualify its formal behavior. We then use these properties to explain experimental results obtained with some of the XML retrieval models.

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Abstract

Summarisation is traditionally used to produce summaries of the textual contents of documents. In this paper, it is argued that summarisation methods can also be applied to the logical structure of XML documents. Structure summarisation selects the most important elements of the logical structure and ensures that the user's attention is focused towards sections, subsections, etc. that are believed to be of particular interest. Structure summaries are shown to users as hierarchical tables of contents. This paper discusses methods for structure summarisation that use various features of XML elements in order to select document portions that a user's attention should be focused to. An evaluation methodology for structure summarisation is also introduced and summarisation results using various summariser versions are presented and compared to one another. We show that data sets used in information retrieval evaluation can be used effectively in order to produce high quality (query independent) structure summaries. We also discuss the choice and effectiveness of particular summariser features with respect to several evaluation measures.

Content

Beitrag in einem Themenheft "Large-Scale and Distributed Systems for Information Retrieval" Vgl.: doi:10.1016/j.ipm.2011.11.002.