Efficient approximation algorithms for adaptive influence maximization
نویسندگان
چکیده
منابع مشابه
Efficient Approximation Algorithms for Point-set Diameter in Higher Dimensions
We study the problem of computing the diameter of a set of $n$ points in $d$-dimensional Euclidean space for a fixed dimension $d$, and propose a new $(1+varepsilon)$-approximation algorithm with $O(n+ 1/varepsilon^{d-1})$ time and $O(n)$ space, where $0 < varepsilonleqslant 1$. We also show that the proposed algorithm can be modified to a $(1+O(varepsilon))$-approximation algorithm with $O(n+...
متن کاملEfficient Greedy Algorithms for Influence Maximization in Social Networks
Influence maximization is an important problem of finding a small subset of nodes in a social network, such that by targeting this set, one will maximize the expected spread of influence in the network. To improve the efficiency of algorithm KK_Greedy proposed by Kempe et al., we propose two improved algorithms, Lv_NewGreedy and Lv_CELF. By combining all of advantages of these two algorithms, w...
متن کاملAdditive Approximation Algorithms for Modularity Maximization
The modularity is a quality function in community detection, which was introduced by Newman and Girvan (2004). Community detection in graphs is now often conducted through modularity maximization: given an undirected graph G = (V,E), we are asked to find a partition C of V that maximizes the modularity. Although numerous algorithms have been developed to date, most of them have no theoretical a...
متن کاملApproximation Algorithms for Free-Label Maximization
Inspired by applications where moving objects have to be labeled, we consider the following (static) point labeling problem: given a set P of n points in the plane and labels that are unit squares, place a label with each point in P in such a way that the number of free labels (labels not intersecting any other label) is maximized. We develop efficient constant-factor approximation algorithms f...
متن کاملExplanation Systems for Influence Maximization Algorithms
The field of influence maximization (IM) has made rapid advances, resulting in many sophisticated algorithms for identifying “influential” members in social networks. However, in order to engender trust in IM algorithms, the rationale behind their choice of “influential” nodes needs to be explained to its users. This is a challenging open problem that needs to be solved before these algorithms ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The VLDB Journal
سال: 2020
ISSN: 1066-8888,0949-877X
DOI: 10.1007/s00778-020-00615-8