Research on Algorithms for Selecting Minimum Seed Set on Location-Aware Social Networks

被引：0
|
作者：
Li Z.-H. [1 ]
Zhang Z.-G. [1 ]
Li J.-Z. [2 ]
机构：
[1] School ofComputer Science and Technology, Heilongjiang University, Harbin
[2] Research Institute of Massive Data Computing, Harbin Institute of Technology, Harbin
来源：
Jisuanji Xuebao/Chinese Journal of Computers | 2017年 / 40卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Geographical position; Influence maximization; J-MIN-Seed problem; Social networks; Tree-based approximate model;
D O I：
10.11897/SP.J.1016.2017.02305
中图分类号：
学科分类号：
摘要：
The goal of the smallest seed set selection problem(J-MIN-Seed problem) is to select a seed set S, at the end of the influence spread, it calls for influencing a certain amount of users (for example J) while the size of S is the smallest. Although the problem has been extensively studied, existing works neglected the fact that the location information can play an important role in J-MIN-Seed problem. In many real-world applications, such as location-aware word-of-mouth marketing, have location-aware requirement. Therefore, we integrate the geographical position factor into J-MIN-Seed problem, and we propose the location-aware J-MIN-Seed problem, and prove that it is NP-hard. One challenge in the problem is how to compute the influence spread of the given region effectively and efficiently. To address this challenge, we extend the existing tree model and design an effective and efficient approximate model. Based on the approximate model, we firstly propose a naive greedy algorithm MS-Greedy. Although MS-Greedy has approximate guarantee, its computation is rather large. In order to meet the needs of online query, we then propose another two effective algorithms Bound-based and Partition-Assembly-based. Experimental results on real data show that our algorithms can solve the location-aware J-MIN-Seed problem effectively. © 2017, Science Press. All right reserved.
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页码：2305 / 2319
页数：14
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