In the last few years, there has been a tremendous change in the way users behave over the net. This is mainly because of the growth that has happened in the field of Web technology. In earlier times, the role a user over the net played was that of an information consumer, now it's more of a data creator role. This role change has benefitted the world of politics, social network analysis, financial market analysis, etc., to name a few. Due to this huge creation of data, a mechanism that can automatically analyze and interpret this opinionated data is badly needed. Toward this research direction, unlike other summarization techniques, the paper proposes a novel method that is unsupervised and also domain-independent for generating opinion summaries. The final summaries that were generated are at four levels that range from being coarse to more granular ones. The proposed technique was tested on various data sets that were from nine different domains. The experimental results clearly indicated that 70-75% of the summaries generated were matching with the manually selected ones.
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