基于概念格融合模型的垃圾评论识别研究

[Purpose/ Significance] In order to effectively solve the dependence and limitation of primitive learners and integrated models on monomorphic specific patterns, this paper expands the classifier into one that can adapt to polymorphic mixed patterns by increasing the observation granularity, with a view to enhancing the model comprehension and classifica⁃ tion ability. [Method/ Process] In this paper, the study replaced the original features with concept sets, introduced the concepts of mutually exclusive concept sets and orthogonal sample sets, separated, generalized and fused the samples, constructed a concept lattice fusion model and evaluated the model in four aspects: model traits, model capability, model quality and overfitting. [Result/ Conclusion] The measurement results with a sample set of 23971 Amazon reviews show that the concept lattice fusion model has a greater improvement in accuracy, stability, and anti-interference, and the mod⁃ el evaluation results indicate that the model has better intrinsic qualities.