Research on Product Reviews Hot Spot Discovery Algorithm Based on Mapreduce

In recent years, with the development of e-commerce, the scale of comment data has shown an exponential growth trend. In this paper, a product review hot spot discovery algorithm based on MapReduce-PR-HD is proposed. The algorithm uses the Vector Space Model to vectorize the text data of the reviews, and utilize the TF-IDF algorithm to calculate the position weight of the feature words, then combines the Canopy algorithm and the K-Means algorithm to achieve the hot spot discovery of product reviews. At the same time, the algorithm obtain the ability to process massive data through the MapReduce framework. Experiments demonstrate that the PR-HD algorithm has high accuracy and parallel efficiency. This allows product developers to obtain more direct and effective suggestions and feedback, which allows product developers to obtain more direct and effective suggestions and feedback.