Fuzzy Set Based Web Opinion Text Clustering Algorithm

With the development of social media, people like to express their views on the Web. Because people express their views casually, which makes the opinion text contain a lot of uncertain and unstructured contents, and it is difficult to cluster the text by normal classification methods. An algorithm of opinion text clustering based on fuzzy set is proposed, which adopts the key words as classifying attributes and calculate the membership degree by fuzzy function, thus can deal with the uncertain and unstructured contents well. Also the algorithm proposed can improve the time and space efficiency, and increase the robustness compared with other classification algorithms.