The Summarization of Commodity Short Comments Based on Topic Clustering
Chengcheng Yu, Ling Shu · Journal of Physics Conference Series · 2019
In recent years, the world economy is being transformed into a digital one. E-commerce has brought a lot of convenience people's life, which is followed by the exponential growth of online reviews of e-commerce. These comments are very valuable for e-commerce and users. This paper proposes an effective method of summarizing short comments information based on Chinese. This method uses a series of phrases composed by noun and adjective as the final presentation. Firstly, the noun and adjective phrases in each comment were extracted, then the LDA probability model was used for content clustering, and finally the content summary of each category was extracted according the frequency of occurrence. In this paper, the real comment data of Taobao is used for experiments, and the results show that the proposed method can effectively summarize valuable information of commodities.