Text classification algorithm of tourist attractions subcategories with modified TF-IDF and Word2Vec.

ABSTRACT: Text classification, as an important research area of text mining, can quickly and effectively extract valuable information to address the challenges of organizing and managing large-scale text data in the era of big data. Currently, the related research on text classification tends to focus on the application in fields such as information filtering, information retrieval, public opinion monitoring, and library and information, with few studies applying text classification methods to the field of tourist attractions. In light of this, a corpus of tourist attraction description texts is constructed using web crawler technology in this paper. We propose a novel text representation method that combines Word2Vec word embeddings with TF-IDF-CRF-POS weighting, optimizing traditional TF-IDF by in

SUBMITTER: Xiao L 

PROVIDER: S-EPMC11488746 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature