In the data-driven era of the internet and business environments,constructing accurate user profiles is paramount for personalized user understanding and *** traditional tf-idfalgorithm has some limitations when eval...
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In the data-driven era of the internet and business environments,constructing accurate user profiles is paramount for personalized user understanding and *** traditional tf-idfalgorithm has some limitations when evaluating the impact of words on classification ***,an improved tf-idf-k algorithm was introduced in this study,which included an equalization factor,aimed at constructing user profiles by processing and analyzing user search *** the training and prediction capabilities of a Support Vector Machine(SVM),it enabled the prediction of user demographic *** experimental results demonstrated that the tf-idf-k algorithm has achieved a significant improvement in classification accuracy and reliability.
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