Abstract
Tagging is one of the most popular services in Web 2.0 and folksonomy is a representation of collaborative tagging. Tag cloud has been the one and only visualization of the folksonomy. The tag cloud, however, provides no information about the relations between tags. In this paper, targeting del.icio.us tag data, we propose a technique, FolksoViz, for automatically deriving semantic relations between tags and for visualizing the tags and their relations. In order to find the equivalence, subsumption, and similarity relations, we apply various rules and models based on the Wikipedia corpus. The derived relations are visualized effectively. The experiment shows that the FolksoViz manages to find the correct semantic relations with high accuracy.
| Original language | English |
|---|---|
| Title of host publication | 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009 |
| Pages | 24-29 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2009 Dec 10 |
| Externally published | Yes |
| Event | 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009 - Daegu, Korea, Republic of Duration: 2009 May 27 → 2009 May 29 |
Publication series
| Name | 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009 |
|---|
Conference
| Conference | 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009 |
|---|---|
| Country | Korea, Republic of |
| City | Daegu |
| Period | 09/5/27 → 09/5/29 |
Fingerprint
Keywords
- Collaborative Tagging
- Folksonomy
- Semantic Relation
- Visualization
- Web 2.0
- Wikipedia
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Hardware and Architecture
- Software
Cite this
FolksoViz : A semantic relation-based folksonomy visualization using the Wikipedia corpus. / Lee, Kangpyo; Kim, Hyun Woo; Shin, Hyopil; Kim, Hyoung Joo.
10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009. 2009. p. 24-29 5286698 (10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - FolksoViz
T2 - A semantic relation-based folksonomy visualization using the Wikipedia corpus
AU - Lee, Kangpyo
AU - Kim, Hyun Woo
AU - Shin, Hyopil
AU - Kim, Hyoung Joo
PY - 2009/12/10
Y1 - 2009/12/10
N2 - Tagging is one of the most popular services in Web 2.0 and folksonomy is a representation of collaborative tagging. Tag cloud has been the one and only visualization of the folksonomy. The tag cloud, however, provides no information about the relations between tags. In this paper, targeting del.icio.us tag data, we propose a technique, FolksoViz, for automatically deriving semantic relations between tags and for visualizing the tags and their relations. In order to find the equivalence, subsumption, and similarity relations, we apply various rules and models based on the Wikipedia corpus. The derived relations are visualized effectively. The experiment shows that the FolksoViz manages to find the correct semantic relations with high accuracy.
AB - Tagging is one of the most popular services in Web 2.0 and folksonomy is a representation of collaborative tagging. Tag cloud has been the one and only visualization of the folksonomy. The tag cloud, however, provides no information about the relations between tags. In this paper, targeting del.icio.us tag data, we propose a technique, FolksoViz, for automatically deriving semantic relations between tags and for visualizing the tags and their relations. In order to find the equivalence, subsumption, and similarity relations, we apply various rules and models based on the Wikipedia corpus. The derived relations are visualized effectively. The experiment shows that the FolksoViz manages to find the correct semantic relations with high accuracy.
KW - Collaborative Tagging
KW - Folksonomy
KW - Semantic Relation
KW - Visualization
KW - Web 2.0
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=71249124070&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71249124070&partnerID=8YFLogxK
U2 - 10.1109/SNPD.2009.80
DO - 10.1109/SNPD.2009.80
M3 - Conference contribution
AN - SCOPUS:71249124070
SN - 9780769536422
T3 - 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009
SP - 24
EP - 29
BT - 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009
ER -