In-Browser Summarisation: Generating Elaborative Summaries Biased Towards the Reading Context

We investigate elaborative summarisation, where the aim is to identify supplementary information that expands upon a key fact. We envisage such summaries being useful when browsing certain kinds of (hyper-)linked document sets, such as Wikipedia articles or repositories of publications linked by citations. For these collections, an elaborative summary is intended to provide additional information on the linking anchor text. Our contribution in this paper focuses on identifying and exploring a real task in which summarisation is situated, realised as an In-Browser tool. We also introduce a neighbourhood scoring heuristic as a means of scoring matches to relevant passages of the document. In a preliminary evaluation using this method, our summarisation system scores above our baselines and achieves a recall of 57% annotated gold standard sentences.