Abstract
Review similarity computing is used to judge whether the content of online reviews is related to the products. It is an important prerequisite to judge the usefulness of reviews, and it is also an important basis for the classification and sorting of product reviews. This paper combines the VSM, TF-IDF algorithm and cosine similarity algorithm to build the model of similarity computing between the product online reviews and product features, and to build the process framework of review similarity computing for enterprises. Besides, this paper also verifies the model’s effectiveness and correctness based on real online review data of E-business. The experiment results show that the process model can be used to quantify the similarity between reviews and product features, and the similarity results also have a good effect on the application of the review sorting.
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