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Textual Distraction as a Basis for Evaluating Automatic Summarisers
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Textual Distraction as a Basis for Evaluating Automatic Summarisers
Our summarisation tool, SEAGULL (Summary Extraction Algorithm Generated Using Lexical Links), is a sentence extractor which exploits the patterns of lexical repetition across a text and creates abridgements which express non-trivially the conceptual content and development of topic. In this paper, we report on a test devised to assess its performance against other summarisers. This involves the introduction of progressive batches of unrelated sentences into a source text. Targeted distraction reveals the relative degrees of robustness in summariser performance. The tests show that our system functions best.
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