TY - GEN
T1 - Tag suggestion method based on association pattern and bigram approach
AU - Kim, Hyunwoo
AU - Lee, Kangpyo
AU - Shin, Hyopil
AU - Kim, Hyoung Joo
PY - 2009
Y1 - 2009
N2 - Recently, the number of articles, blog posts, photos and videos on the web is dramatically increasing because of the increase of internet usage. In this situation, the web search is the most important thing in the web. When we search, we can use text information from articles or blog posts. In the case of photos and videos, we can only use a title. If there are tags - significant keywords of that multimedia, we can use tag information to search. Tag is a keyword of text, blog post, or multimedia. Users have already recognized about the value and importance of tags but only a few users are using tags. They might be annoying to add tags or they don't know what to add for good search result. This is why tag suggestion system is needed. Our method analyzes crawled tag data and suggests appropriate tags to user using association pattern and bigram approach. By experiments, we conclude that our tag suggestion method suggests appropriate tags.
AB - Recently, the number of articles, blog posts, photos and videos on the web is dramatically increasing because of the increase of internet usage. In this situation, the web search is the most important thing in the web. When we search, we can use text information from articles or blog posts. In the case of photos and videos, we can only use a title. If there are tags - significant keywords of that multimedia, we can use tag information to search. Tag is a keyword of text, blog post, or multimedia. Users have already recognized about the value and importance of tags but only a few users are using tags. They might be annoying to add tags or they don't know what to add for good search result. This is why tag suggestion system is needed. Our method analyzes crawled tag data and suggests appropriate tags to user using association pattern and bigram approach. By experiments, we conclude that our tag suggestion method suggests appropriate tags.
KW - Association pattern
KW - Bigram
KW - Folksonomy
KW - Tag suggestion
KW - Web 2.0
UR - http://www.scopus.com/inward/record.url?scp=71249157775&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71249157775&partnerID=8YFLogxK
U2 - 10.1109/SNPD.2009.72
DO - 10.1109/SNPD.2009.72
M3 - Conference contribution
AN - SCOPUS:71249157775
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 - 63
EP - 68
BT - 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009
T2 - 10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009
Y2 - 27 May 2009 through 29 May 2009
ER -