A Method of Event Sentiment Classification Based on Text Similarity
A text similarity and sentiment classification technology, applied in text database clustering/classification, text database query, unstructured text data retrieval and other directions, can solve the problems of heavy monitoring workload, difficult text monitoring, etc. Effects of parameters
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[0047] A text similarity-based event sentiment classification method, comprising the following steps,
[0048] S001, use the text similarity clustering algorithm to cluster the text set into event A, and analyze all the texts in event A, that is, θ is 100%; here, the value of θ can also be other values, mainly for the analysis of text to determine;
[0049] There are three records in event A, which are:
[0050] R1: The dream of national rejuvenation of Chinese sons and daughters vol1: 10000;
[0051] R2: The Great Revival of Chinese Famous Clan vol2: 2000;
[0052] R3: As Chinese sons and daughters with dreams, we will move forward without hesitation vol3: 1000;
[0053] S002, using the trained vector model M to generate respective 300-dimensional vectors v1, V2, V3 of the text in the event A,
[0054]v1=M(r1)=[0.11,0.04,-0.12,…,-0.11,-0.03]
[0055] v2=M(r2)=[-0.05,-0.18,-0.15,…,-0.05,0.21]
[0056] v3=M(r3)=[-0.18,0.22,-0.18,…,-0.08,0.02]
[0057] S003, according to ...
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