The effects of analysing cohesion on document summarisation

We argue that in general, the analysis of lexical cohesion factors in a document can drive a summarizer, as well as enable other content characterization tasks. More narrowly, this paper focuses on how one particular cohesion factor—simple lexical repetition—can enhance an existing sentence extraction summarizer, by enabling strategies for overcoming some particularly jarring enduser effects in the summaries, typically due to coherence degradation, readability deterioration, and topical under-representation. Lexical repetition is instrumental to, among other things, the topical make-up of a text, and in our framework a lexical repetition-based model of discourse segmentation, capable of detecting topic shifts, is integrated with a linguistically-aware summarizer utilizing notions of salience and dynamically-adjustable summary size. We show that even by leveraging lexical repetition alone, summaries are of comparable, and under certain conditions better, quality than the ones delivered by a state-of-the-art summarizer. This is encouraging for a broad research platform focusing on the recognition and use of cohesive devices in text for a range of content characterisation and document management tasks.