원문정보
보안공학연구지원센터(IJGDC)
International Journal of Grid and Distributed Computing
Vol.7 No.3
2014.06
pp.41-48
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Clustering of Weibo users is one of the most important topics in data mining on social network. Clustering can help dig out the relations among people or between people and resources. A lot of work relating to clustering has been done on analyzing personal relationship, whereas we focus our clustering model on preferences and interests. In this article, we propose a new clustering model focusing on users’ tags people choose to describe themselves. First, we will study the characteristics of Sina Weibo tags of users, which are the foundation of the new clustering model. Second, we will use the word2vec tool to cluster Weibo users based on their tags and verify the accuracy of the results.
목차
Abstract
1. Introduction
2. Related Work
2.1. Tag Clustering
2.2. Word2vec
3. Study of Weibo Users’ Tags
3.1. Suitable
3.2. Long Tail
3.3. Ambiguity
4. Clustering Using Word2vec Tool
4.1. Similarity Measures
4.2. Tag Clustering and Result Analysis
5. Clustering Validity
6. Conclusion and Future Work
References
1. Introduction
2. Related Work
2.1. Tag Clustering
2.2. Word2vec
3. Study of Weibo Users’ Tags
3.1. Suitable
3.2. Long Tail
3.3. Ambiguity
4. Clustering Using Word2vec Tool
4.1. Similarity Measures
4.2. Tag Clustering and Result Analysis
5. Clustering Validity
6. Conclusion and Future Work
References
저자정보
참고문헌
자료제공 : 네이버학술정보