Design of a User Comment Management System Based on Text Mining

Presently, text mining in e-commerce reviews predominantly focus on singular sentiment analysis, yet constraints persist score computation, semantic inclination discernment, and lexicon construction. To address these limitations, this study establishes an user comment management system based mining. It performs part-of-speech tagging dependency grammar analysis the historical corpus of e-commerce, unveiling collocations that potentially convey users' emotive predispositions. Subsequently, a rule table is formulated for extraction emotional words. The enhanced BiGRU model employed bidirectional textual features, which are subsequently fused with TextCNN model. Test results evince effectively accomplishes desired objectives, positive comments attaining accuracy recall rates 93.49% 96.98%, respectively, thereby mitigating drawbacks associated laborious operations inadequate precision inherent extant systems.