Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions

The Opinosis Summarization framework focuses on generating very short abstractive summaries from large amounts of text. These summaries can resemble micropinions or “micro-reviews” that you see on sites like twitter and four squares. The idea of the algorithm is to use a word graph data structure referred to as the Opinosis-Graph to represent the text to be summarized. Then, the resulting graph is repeatedly explored to find meaningful paths which in turn becomes candidate summary phrases.

Opinosis Dataset – Topic related review sentences

This dataset contains sentences extracted from user reviews on a given topic. Example topics are “performance of Toyota Camry” and “sound quality of ipod nano”, etc. In total there are 51 such topics  with each topic having approximately 100 sentences (on average). The reviews were obtained from various sources – Tripadvisor (hotels), Edmunds.com (cars) and Amazon.com (various electronics).  This dataset was used for the following automatic text summarization project .