Title :
Multi-threshold Ranking Model Based on Naive Bayes for Community-Ranked Article Submission Sites
Author :
Liu, Nianzu ; Xu, Guanglin ; Liu, Yongchang
Author_Institution :
Sch. of Math. & Inf., Shanghai Lixin Univ. of Commerce, Shanghai, China
Abstract :
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.
Keywords :
Bayes methods; pattern classification; social networking (online); community ranked article submission site; multithreshold ranking model; naive Bayes; user preference classification; Classification algorithms; Educational institutions; Electronic mail; Focusing; Mathematical model; Set theory; Software algorithms; Multi-threshold; Ranking;
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
DOI :
10.1109/GrC.2010.45
