TY  - CONF
ID  - www2009178
UR  - http://www2009.eprints.org/178/
A1  - Zhu, Junyan
A1  - Wang, Can
A1  - He, Xiaofei
A1  - Bu, Jiajun
A1  - Chen, Chun
A1  - Shang, Shujie
A1  - Qu, Mingcheng
A1  - Lu, Gang
Y1  - 2009/04//
N2  - Social annotations on a Web document are highly generalized description of topics contained in that page. Their tagged frequency indicates the user attentions with various degrees. This makes annotations a good resource for summarizing multiple topics in a Web page. In this paper, we present a tag-oriented Web document summarization approach by using both document content and the tags annotated on that document. To improve summarization performance, a new tag ranking algorithm named EigenTag is proposed in this paper to reduce noise in tags. Meanwhile, association mining technique is employed to expand tag set to tackle the sparsity problem. Experimental results show our tag-oriented summarization has a signi?cant improvement over those not using tags.
TI  - Tag-Oriented Document Summarization
SP  - 1195
M2  - Madrid, Spain
AV  - public
EP  - 1195
T2  - 18th International World Wide Web Conference
ER  -