Name
Abstract | ||
|---|---|---|
It is difficult to understand the outline of community-type content such as Blog, Social Network Services(SNS), and Bulletin Board System(BBS) because multiple users post content freely. In this paper, we have developed a system that presents the outline of community-type content by using Wikipedia. We focus on the table of contents (TOC) collected from Wikipedia. Our system compares the comments in a thread with the information in the TOC obtained from Wikipedia and identifies contents that are similar. Thus, the user can understand the outline of community-type content when he/she views a table with similar contents. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-12098-5_36 | DASFAA (2) |
Keywords | Field | DocType |
community-type content,social network services,multiple users post content,similar content,bulletin board system,table of contents | Data mining,World Wide Web,Social network,Bulletin board system,Computer science,Table of contents,Database | Conference |
Volume | ISSN | ISBN |
5982 | 0302-9743 | 3-642-12097-0 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Akiyo Nadamoto | 1 | 189 | 34.24 |
| Eiji Aramaki | 2 | 371 | 45.89 |
| Takeshi Abekawa | 3 | 48 | 10.35 |
| Yohei Murakami | 4 | 284 | 42.25 |