While there is a large overlap between text summarization and review opinion mining, most work focuses on sentiment-oriented aspect extraction and the output is usually a set of topics words plus their representative text units (Hu and Liu, 2004;Zhuang et al., 2006).
such a topic-based summarization framework is beyond the focus of our work, as we aim to adapt traditional extractive techniques to the review domain by introducing review helpfulness ratings as guidance.