Multi-threshold Ranking Model Based on Naive Bayes for Community-Ranked Article Submission Sites

摘要

Pertinent to the preference of ranking algorithm of recent Community-Ranked Article Submission Sites, this paper gives a set of models of user preference classification and multi-threshold ranking algorithm based on Naive Bayes and thus provides a new ranking algorithm for similar Community-Ranked Article Submission Sites. The paper shows more reasonable ranking results in practice, which effectively testify the reasonability of such algorithm.