Helpfulness-Guided Review Summarization
نویسنده
چکیده
Review mining and summarization has been a hot topic for the past decade. A lot of effort has been devoted to aspect detection and sentiment analysis under the assumption that every review has the same utility for related tasks. However, reviews are not equally helpful as indicated by user-provided helpfulness assessment associated with the reviews. In this thesis, we propose a novel review summarization framework which summarizes review content under the supervision of automated assessment of review helpfulness. This helpfulness-guided framework can be easily adapted to traditional review summarization tasks, for a wide range of domains.
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