Abstract
With the arrival of the big data era, a large amount of text data has grown exponentially, and text topic mining has become a challenging task. Text topic knowledge mining based on co-word analysis can not deeply discover the semantic relationship between keywords, while LDA model misses the important information of document keyword structure. Therefore, this paper proposes a text topic mining algorithm based on spatial propagation similarity metrics. Based on the co-occurrence matrix, the spatial propagation similarity metric algorithm is used to calculate the inter-word relationship, and further cluster analysis is carried out, aiming at deeper mining of text themes.
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