TY - GEN
T1 - Utilizing SSTAG
T2 - 11th IEEE International Conference on Computer and Information Technology, CIT 2011 and 11th IEEE International Conference on Scalable Computing and Communications, SCALCOM 2011
AU - He, Guijia
AU - Zhang, Tao
AU - Lee, Byungjeong
AU - Kim, Jin Suk
PY - 2011
Y1 - 2011
N2 - As a social bookmark tool, Folksonomy gives high freedom to users and allows users to share and notate resources. However, many tags applied arbitrarily by users can not really reflect the contents of web pages and lead to ineffectiveness in information retrieval. Moreover, there are still some important tasks about how to eliminate ambiguity more easily and recommend more interested web pages to users. To resolve the above problems, we propose a novel mechanism named SSTAG, and it can recommend a set of Super-tags to users for their choices based on keywords input. As various topics related to the keywords, the Super-tags are selected from different clusters of web pages related to the keywords. A user chooses a Super-tag, which means the user may have chosen an interested topic, and then some more detailed tags in the topic are recommended as Sub-tags. The relationship between Super-tag and Sub-tag is just like navigation and positioning. Likewise, the user can choose one Sub-tag and submit it with the Super-tag. By means of the user's choice, this system can capture users' preference and recommend a series of related web pages. We employ a real world dataset to examine the mechanism, and the experimental results show that this mechanism can eliminate ambiguity efficiently and recommend a set of appropriate tags.
AB - As a social bookmark tool, Folksonomy gives high freedom to users and allows users to share and notate resources. However, many tags applied arbitrarily by users can not really reflect the contents of web pages and lead to ineffectiveness in information retrieval. Moreover, there are still some important tasks about how to eliminate ambiguity more easily and recommend more interested web pages to users. To resolve the above problems, we propose a novel mechanism named SSTAG, and it can recommend a set of Super-tags to users for their choices based on keywords input. As various topics related to the keywords, the Super-tags are selected from different clusters of web pages related to the keywords. A user chooses a Super-tag, which means the user may have chosen an interested topic, and then some more detailed tags in the topic are recommended as Sub-tags. The relationship between Super-tag and Sub-tag is just like navigation and positioning. Likewise, the user can choose one Sub-tag and submit it with the Super-tag. By means of the user's choice, this system can capture users' preference and recommend a series of related web pages. We employ a real world dataset to examine the mechanism, and the experimental results show that this mechanism can eliminate ambiguity efficiently and recommend a set of appropriate tags.
KW - Information retrieval
KW - Tag recommendation
KW - Web page search
UR - http://www.scopus.com/inward/record.url?scp=80055016141&partnerID=8YFLogxK
U2 - 10.1109/CIT.2011.85
DO - 10.1109/CIT.2011.85
M3 - Conference contribution
AN - SCOPUS:80055016141
SN - 9780769543888
T3 - Proceedings - 11th IEEE International Conference on Computer and Information Technology, CIT 2011
SP - 455
EP - 460
BT - Proceedings - 11th IEEE International Conference on Computer and Information Technology, CIT 2011
Y2 - 31 August 2011 through 2 September 2011
ER -