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2016³â µ¿°èÇмú¹ßǥȸ
2016³â µ¿°èÇмú¹ßǥȸ
Current Result Document :
14
/ 22
ÀÌÀü°Ç
´ÙÀ½°Ç
ÇѱÛÁ¦¸ñ(Korean Title)
Threshold Estimation Models for Influence Maximization in Social Network
¿µ¹®Á¦¸ñ(English Title)
Threshold Estimation Models for Influence Maximization in Social Network
ÀúÀÚ(Author)
Ashis Talukder
Md. Golam Rabiul Alam
Anupam Kumar Bairagi
Sarder Fakrul Abedin
Hoang T. Nguyen
Choong Seon Hong
¿ø¹®¼ö·Ïó(Citation)
VOL 43 NO. 02 PP. 0888 ~ 0890 (2016. 12)
Çѱ۳»¿ë
(Korean Abstract)
¿µ¹®³»¿ë
(English Abstract)
The Influence Maximization (IM) problem determines a small set of influential users that maximizes the influence spread in the network where influence is measured by the number of active nodes. Among the two classical models, in the Linear Threshold (LT) a node is activated if the total influence of all the active in-neighbors is no less than a given threshold and thus threshold selection is important. In this research we observe that the threshold depends on the application of IM and the influence weight. Then we propose different threshold models based on influence weight. Our models are linear and the simulation on real dataset shows that they have fast running time.
Å°¿öµå(Keyword)
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