Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Influence Maximization in Continuous Time Diffusion Networks   The problem of finding the optimal set of source nodes in a diffusion network
that maximizes the spread of information, influence, and diseases in a limited
amount of time depends dramatically on the underlying temporal dynamics of the
network. However, this still remains largely unexplored to date. To this end,
given a network and its temporal dynamics, we first describe how continuous
time Markov chains allow us to analytically compute the average total number of
nodes reached by a diffusion process starting in a set of source nodes. We then
show that selecting the set of most influential source nodes in the continuous
time influence maximization problem is NP-hard and develop an efficient
approximation algorithm with provable near-optimal performance. Experiments on
synthetic and real diffusion networks show that our algorithm outperforms other
state of the art algorithms by at least ~20% and is robust across different
network topologies.

35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
7
The categories of this paper are: hep-th