Topic Models for Summarizing Novelty
نویسندگان
چکیده
We define temporal summaries of news stories as extracting as few sentences as possible from each event within a news topic, where the stories are presented one at a time and sentences from a story must be ranked before the next story can be considered. We outline an evaluation strategy that we have developed for this task and describe simple language models for capturing novelty and usefulness in the context of summarization. We show that the simple approaches work moderately well, and outline our ideas for moving forward.
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