TY  - CONF
AU  - Li, Xin
AU  - Guo, Lei
AU  - Zhao, Yihong E.
A2  - 
T1  - Tag-based Social Interest Discovery
T2  - Proceedings of the 17th International World Wide Web Conference
PB  - ACM
CY  - 
PY  - 2008/
M2  - 
VL  - 
IS  - 
SP  - 675
EP  - 684
UR  - http://www2008.org/papers/pdf/p675-liA.pdf
M3  - 
KW  - ***
KW  - association
KW  - clustering
KW  - community
KW  - del.icio.us
KW  - detection
KW  - folksonomy
KW  - rules
L1  - 
SN  - 
N1  - 
N1  - 
AB  - The success and popularity of social network systems, such as del.icio.us, Facebook, MySpace, and YouTube, have generated many interesting and challenging problems to the research community. Among others, discovering social interests shared by groups of users is very important because it helps to connect people with common interests and encourages people to contribute and share more contents. The main challenge to solving this problem comes from the diffi- culty of detecting and representing the interest of the users. The existing approaches are all based on the online connections of users and so unable to identify the common interest of users who have no online connections. In this paper, we propose a novel social interest discovery approach based on user-generated tags. Our approach is motivated by the key observation that in a social network, human users tend to use descriptive tags to annotate the contents that they are interested in. Our analysis on a large amount of real-world traces reveals that in general, user-generated tags are consistent with the web content they are attached to, while more concise and closer to the understanding and judgments of human users about the content. Thus, patterns of frequent co-occurrences of user tags can be used to characterize and capture topics of user interests. We have developed an Internet Social Interest Discovery system, ISID, to discover the common user interests and cluster users and their saved URLs by different interest topics. Our evaluation shows that ISID can effectively cluster similar documents by interest topics and discover user communities with common interests no matter if they have any online connections.
ER  -

TY  - CONF
AU  - Schmitz, Christoph
AU  - Hotho, Andreas
AU  - Jäschke, Robert
AU  - Stumme, Gerd
A2  - Batagelj, V.
A2  - Bock, H.-H.
A2  - Ferligoj, A.
A2  - Žiberna, A.
T1  - Mining Association Rules in Folksonomies
T2  - Data Science and Classification (Proc. IFCS 2006 Conference)
PB  - Springer
CY  - Berlin/Heidelberg
PY  - 2006/07
M2  - 
VL  - 
IS  - 
SP  - 261
EP  - 270
UR  - http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006asso_ifcs.pdf
M3  - 10.1007/3-540-34416-0_28
KW  - 2006
KW  - analysis
KW  - association
KW  - folksonomy
KW  - kdubiq
KW  - myown
KW  - network
KW  - rules
KW  - semantic
KW  - seminar2006
KW  - sosbuch
KW  - summerschool
L1  - 
SN  - 978-3-540-34415-5
N1  - 
N1  - 
AB  - 
ER  -

TY  - CONF
AU  - Ng, Raymond T.
AU  - Lakshmanan, Laks V. S.
AU  - Han, Jiawei
AU  - Pang, Alex
A2  - 
T1  - Exploratory Mining and Pruning Optimizations of Constrained Association Rules.
T2  - SIGMOD Conference
PB  - 
CY  - 
PY  - 1998/
M2  - 
VL  - 
IS  - 
SP  - 13
EP  - 24
UR  - http://dblp.uni-trier.de/db/conf/sigmod/sigmod98.html#NgLHP98
M3  - 
KW  - 2006
KW  - lecture
KW  - rules
KW  - association
KW  - constraints
KW  - kdd
KW  - mining
L1  - 
SN  - 
N1  - dblp
N1  - 
AB  - 
ER  -

TY  - JOUR
AU  - Park, J.S.
AU  - Chen, M.S.
AU  - Yu, P.S.
T1  - An effective hash-based algorithm for mining association rules
JO  - Proceedings of the 1995 ACM SIGMOD international conference on Management of data
PY  - 1995/
VL  - 
IS  - 
SP  - 175
EP  - 186
UR  - 
M3  - 
KW  - 2006
KW  - table
KW  - lecture
KW  - rules
KW  - association
KW  - kdd
KW  - mining
KW  - hash
L1  - 
SN  - 
N1  - 
N1  - 
AB  - 
ER  -

TY  - CONF
AU  - Srikant, R.
AU  - Agrawal, R.
A2  - 
T1  - Mining Generalized Association Rules
T2  - Proceedings of the 21st International Conference on Very Large Databases
PB  - 
CY  - 
PY  - 1995/10
M2  - 
VL  - 
IS  - 
SP  - 407
EP  - 419
UR  - 
M3  - 
KW  - generalized
KW  - rules
KW  - association
KW  - mining
L1  - 
SN  - 
N1  - 
N1  - 
AB  - 
ER  -

TY  - CONF
AU  - Agrawal, Rakesh
AU  - Imielinski, Tomasz
AU  - Swami, Arun
A2  - 
T1  - Mining association rules between sets of items in large databases
T2  - SIGMOD '93: Proceedings of the 1993 ACM SIGMOD international conference on Management of data
PB  - ACM Press
CY  - New York, NY, USA
PY  - 1993/
M2  - 
VL  - 
IS  - 
SP  - 207
EP  - 216
UR  - 
M3  - 
KW  - association
KW  - basic
KW  - mining
KW  - ml
KW  - rules
L1  - 
SN  - 
N1  - Mining association rules between sets of items in large databases
N1  - 
AB  - 
ER  -