Topic Structure Mining Using PageRank Without Hyperlinks

Toda, Hiroyuki; Fujimura, Kikuo; Kataoka, Ryuho; Kitagawa, Hiroyuki

doi:10.1007/11931584_18

Search citation statements

Order By: Relevance

Paper Sections

Select...

Construction Of Graph Structure1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2008

Publication Types

Select...

Other1

Relationship

Self Cite1

Independent0

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The links with very small similarity weight are not necessary and the 2nd operation removes them. [12] …”

Section: Construction Of Graph Structurementioning

confidence: 97%

Topic structure mining using temporal co-occurrence

Toda

Kitagawa

Fujimura

et al. 2008

Proceedings of the 2nd International Conference on Ubiquitous Information Management and Communication

Self Cite

View full text Add to dashboard Cite

This paper proposes a topic structure mining method for document sets that include time stamps. Topic structure mining is a text mining method that uses the graph structure that represents the document pair similarities in the document set. This method yields not only topic extraction from documents and clustering of documents but also extracts the relationship between clusters and the meaning of each document in the cluster. Our method combines temporal co-occurrence with document similarity in constructing the graph structure. We also report evaluation results and the effectiveness of the proposed method.

show abstract

“…The links with very small similarity weight are not necessary and the 2nd operation removes them. [12] …”

Section: Construction Of Graph Structurementioning

confidence: 97%