Generating Concise and Readable Summaries of XML Documents

TL;DR

This paper presents methods for generating concise, readable, and meaningful summaries of XML documents, helping users understand large XML data collections efficiently.

Contribution

It introduces techniques to identify important XML tags and text units, and to generate summaries of varying sizes, validated through user studies on real datasets.

Findings

Methods effectively identify key information in XML documents

Summaries assist users in understanding large XML datasets

User studies confirm the usefulness of the proposed approach

Abstract

XML has become the de-facto standard for data representation and exchange, resulting in large scale repositories and warehouses of XML data. In order for users to understand and explore these large collections, a summarized, bird's eye view of the available data is a necessity. In this paper, we are interested in semantic XML document summaries which present the "important" information available in an XML document to the user. In the best case, such a summary is a concise replacement for the original document itself. At the other extreme, it should at least help the user make an informed choice as to the relevance of the document to his needs. In this paper, we address the two main issues which arise in producing such meaningful and concise summaries: i) which tags or text units are important and should be included in the summary, ii) how to generate summaries of different sizes.%for different memory budgets. We conduct user studies with different real-life datasets and show that our methods are useful and effective in practice.