News Story Gisting at University College Dublin
نویسندگان
چکیده
In this paper we present a machine learning approach to generating very short news story summaries (i.e. no more than 75 bytes long). Our technique uses a decision tree classifier to establish which phrases in a text should be included in the resultant summary. Our ROUGE evaluation results for task 1 (English text summarisation) and task 3 (translated Arabic text summarisation) indicate that this technique is an adequate solution to this problem.
منابع مشابه
Broadcast News Gisting Using Lexical Cohesion Analysis
In this paper we describe an extractive method of creating very short summaries or gists that capture the essence of a news story using a linguistic technique called lexical chaining. The recent interest in robust gisting and title generation techniques originates from a need to improve the indexing and browsing capabilities of interactive digital multimedia systems. More specifically these sys...
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