Title :
Method of tags recommendation for blogs: A comparative study
Author :
Tang, Li-juan ; Zhang, Cheng-zhi
Author_Institution :
Dept. of Inf. Manage., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
Tags are products of Web 2.0. They play an important role in user modeling, friends or information recommendation. In this paper, keywords from blogs are extracted by using TextRank and TF*IDF algorithms respectively. The keywords are used to tag recommendation. Experiment results show that the performance of these two algorithms is very closely.
Keywords :
Internet; Web sites; recommender systems; TextRank; Web 2.0; blogs; information recommendation; tags recommendation; user modeling; Abstracts; Blogs; Electronic mail; Social tagging; TF*IDF; Tags recommendation; TextRank;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
Print_ISBN :
978-1-4673-1484-8
DOI :
10.1109/ICMLC.2012.6359689
