TY - GEN
T1 - Link prediction across multiple social networks
AU - Ahmad, Muhammad Aurangzeb
AU - Borbora, Zoheb
AU - Srivastava, Jaideep
AU - Contractor, Noshir
PY - 2010/12/1
Y1 - 2010/12/1
N2 - The problem of link prediction has been studied extensively in literature. There are various versions of the link prediction problem e.g., link existence problem, link removal problem, predicting edge weights over time etc. In this paper we describe a new type of link prediction problem called the Inter-network link-prediction problem where the task is to predict links across different networks. Thus given a set of nodes which participate in multiple networks the task is to determine if one can predict the edges that occur in one network by only using node attribute and edge information from other networks. We use insights from theories of evolution of social communication networks and the MTML framework to derive models which can be used to make link predictions across networks. For the experiments data from different types of social networks from a Massively Multiplayer Online Role Playing Game (MMORPG) is used.
AB - The problem of link prediction has been studied extensively in literature. There are various versions of the link prediction problem e.g., link existence problem, link removal problem, predicting edge weights over time etc. In this paper we describe a new type of link prediction problem called the Inter-network link-prediction problem where the task is to predict links across different networks. Thus given a set of nodes which participate in multiple networks the task is to determine if one can predict the edges that occur in one network by only using node attribute and edge information from other networks. We use insights from theories of evolution of social communication networks and the MTML framework to derive models which can be used to make link predictions across networks. For the experiments data from different types of social networks from a Massively Multiplayer Online Role Playing Game (MMORPG) is used.
KW - Inter-network link prediction
KW - Link prediction
KW - Multiple social networks
KW - Social networks
UR - http://www.scopus.com/inward/record.url?scp=79951739653&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79951739653&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2010.79
DO - 10.1109/ICDMW.2010.79
M3 - Conference contribution
AN - SCOPUS:79951739653
SN - 9780769542577
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 911
EP - 918
BT - Proceedings - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
T2 - 10th IEEE International Conference on Data Mining Workshops, ICDMW 2010
Y2 - 14 December 2010 through 17 December 2010
ER -