scirs2_graph/diffusion/
mod.rs

1//! Information diffusion models and influence maximization algorithms
2//!
3//! This module provides:
4//!
5//! - **Diffusion Models**: Independent Cascade (IC), Linear Threshold (LT),
6//!   SIR (Susceptible-Infected-Recovered), and SIS epidemic models.
7//! - **Influence Maximization**: Greedy Monte-Carlo (Kempe 2003), CELF, CELF++,
8//!   and fast heuristics (high-degree, PageRank).
9//! - **Reverse Influence Sampling**: RIS sets, RIS-based estimators, the IMM
10//!   algorithm (Tang et al. 2014/2015), and the Sandwich approximation.
11//!
12//! # References
13//!
14//! - Kempe, D., Kleinberg, J., & Tardos, É. (2003). Maximizing the Spread of
15//!   Influence through a Social Network. *KDD 2003*.
16//! - Leskovec, J., Krause, A., Guestrin, C., Faloutsos, C., VanBriesen, J.,
17//!   & Glance, N. (2007). Cost-effective Outbreak Detection in Networks. *KDD
18//!   2007*. (CELF)
19//! - Goyal, A., Lu, W., & Lakshmanan, L. V. S. (2011). CELF++. *WWW 2011*.
20//! - Tang, Y., Xiao, X., & Shi, Y. (2014). Influence Maximization: Near-Optimal
21//!   Time Complexity Meets Practical Efficiency. *SIGMOD 2014*. (IMM)
22//! - Borg, I., & Groenen, P. (2005). Sandwich approximation for submodular
23//!   maximization.
24
25pub mod influence_max;
26pub mod models;
27pub mod ris;
28
29pub use influence_max::{
30    celf_influence_max, celf_plus_plus, degree_heuristic, greedy_influence_max, pagerank_heuristic,
31    InfluenceMaxConfig, InfluenceMaxResult,
32};
33pub use models::{
34    expected_spread, simulate_ic, simulate_lt, simulate_sir, simulate_sis, IndependentCascade,
35    LinearThreshold, SIRModel, SISModel, SimulationResult, SirState,
36};
37pub use ris::{
38    generate_rr_sets, imm_algorithm, ris_estimate, sandwich_approximation, ImmConfig, ImmResult,
39    RISConfig, RRSet,
40};
scirs2_graph/diffusion/mod.rs

scirs2_graph/diffusion/
mod.rs
