TY - GEN

T1 - Cross-tagging for personalized open social networking

AU - Stewart, Avaré

AU - Diaz-Aviles, Ernesto

AU - Nejdl, Wolfgang

AU - Marinho, Leandro Balby

AU - Nanopoulos, Alexandros

AU - Schmidt-Thieme, Lars

PY - 2009/6/29

Y1 - 2009/6/29

N2 - The Social Web is successfully established and poised for continued growth. Web 2.0 applications such as blogs, bookmarking, music, photo and video sharing systems are among the most popular; and all of them incorporate a social aspect, i.e., users can easily share information with other users. But due to the diversity of these applications - serving different aims - the Social Web is ironically divided. Blog users who write about music for example, could possibly benefit from other users registered in other social systems operating within the same domain, such as a social radio station. Although these sites are two different and disconnected systems, offering distinct services to the users, the fact that domains are compatible could benefit users from both systems with interesting and multi-faceted information. In this paper we propose to automatically establish social links between distinct social systems through cross-tagging, i.e., enriching a social system with the tags of other similar social system(s). Since tags are known for increasing the prediction quality of recommender systems (RS), we propose to quantitatively evaluate the extent to which users can benefit from cross-tagging by measuring the impact of different cross-tagging approaches on tag-aware RS for personalized resource recommendations. We conduct experiments in real world data sets and empirically show the effectiveness of our approaches.

AB - The Social Web is successfully established and poised for continued growth. Web 2.0 applications such as blogs, bookmarking, music, photo and video sharing systems are among the most popular; and all of them incorporate a social aspect, i.e., users can easily share information with other users. But due to the diversity of these applications - serving different aims - the Social Web is ironically divided. Blog users who write about music for example, could possibly benefit from other users registered in other social systems operating within the same domain, such as a social radio station. Although these sites are two different and disconnected systems, offering distinct services to the users, the fact that domains are compatible could benefit users from both systems with interesting and multi-faceted information. In this paper we propose to automatically establish social links between distinct social systems through cross-tagging, i.e., enriching a social system with the tags of other similar social system(s). Since tags are known for increasing the prediction quality of recommender systems (RS), we propose to quantitatively evaluate the extent to which users can benefit from cross-tagging by measuring the impact of different cross-tagging approaches on tag-aware RS for personalized resource recommendations. We conduct experiments in real world data sets and empirically show the effectiveness of our approaches.

KW - Recommender systems

KW - Social media

KW - Tags

KW - Web 2.0

UR - http://www.scopus.com/inward/record.url?scp=70450169650&partnerID=8YFLogxK

U2 - 10.1145/1557914.1557960

DO - 10.1145/1557914.1557960

M3 - Conference contribution

AN - SCOPUS:70450169650

SN - 9781605584867

T3 - Proceedings of the 20th ACM Conference on Hypertext and Hypermedia, HT'09

SP - 271

EP - 278

BT - Proceedings of the 20th ACM Conference on Hypertext and Hypermedia, HT'09

PB - Association for Computing Machinery (ACM)

T2 - 20th ACM Conference on Hypertext and Hypermedia, HT'09

Y2 - 29 June 2009 through 1 July 2009

ER -