Opinion Mining Using Frequent Pattern Growth Method from Unstructured Text

In the last one decade, the area of opinion mining has experienced a major growth because of the increase in online unstructured data which are contributed by reviewers over different topics and subjects. These data sometimes become important for users who want to take their decision based on opinions of actual users of the product. In this paper, we present the FP-growth method for frequent pattern mining from review documents which act as a backbone for mining the opinion words along with their relevant features by experimental data over two different domains which are very different in their nature.