| Summary: | It is an important problem of identifying and quantifying the competition in similar services or products in the research area of competitive relationship mining. A scientific and reasonable evaluation metric of competitive relationship is proposed, and a comprehensive evaluation system of entity competitive relationship is constructed. Dimension reduction and theme extraction on users reviews are achieved by using the latent Dirichlet allocation (LDA) model, the similarity function of comments is constructed, and the similarity degree of entity users comments is quantified. Based on the geographic location information of entities, the spatial distance of entities is calculated, the adjacent relation of entities is constructed, the distance of entities with adjacent relationship is regarded as the cluster center, and the entities are clustered by using the K-nearest neighbor (KNN) algorithm. The location & topical model (LTM) is proposed by integrating user's reviews, entity's geographical attributes, and quantifying the com-petitive relationship between entities. Conducted on a large number of real social network data, the experiments results show that the proposed method has great advantages in quantitative metric formulation, practicability and time performance.
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