Summarisation of the logical structure of XML documents

• Published in: Information processing & management Vol. 48; no. 5; pp. 956 - 968
• Main Authors: Szlávik, Zoltán, Tombros, Anastasios, Lalmas, Mounia
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.09.2012; Elsevier; Elsevier Science Ltd
• Subjects: Automatic abstracting; Data processing; Exact sciences and technology; Extensible Markup Language; Information and communication sciences; Information processing; Information processing and retrieval; Information retrieval; Information retrieval. Man machine relationship; Information science. Documentation; Methods; Query processing; Research process. Evaluation; Sciences and techniques of general use; Structure summarisation; Studies; Summaries; Tables; Users; XML; XML retrieval; Structure summarisation; XML retrieval
• ISSN: 0306-4573; 1873-5371
• DOI: 10.1016/j.ipm.2011.11.002

► We investigate the summarisation of the logical structure of XML documents. ► The structure is summarised using a method inspired by extractive text summarisation. ► We discuss and evaluate features used in structure summary generation. ► We present and compare ways to evaluate structure summaries. 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.