A social network consists of a set of members and social relations among these members. Network integration refers to the situation when ties are established between members of two social networks. This corresponds to a process of "dissolving" two networks into a single entity. Real-life examples of network integration include mergers and acquisitions of companies, or collaboration between research teams. Here, a crucial question is how a small number of relations could be established that allows the resulting network to have certain desirable togetherness properties (such as smooth information flow between the two component networks). This project investigates network integration as an AI problem. The goal is to study efficient heuristics that computes near-optimal results and how random network models impact their performance.
Undergraduate
Upon completion of the project, the students are expected to produce
- efficient heuristics for finding solutions of network integration problem (and its variants)
- software tools that implements the heuristics above
- critical analysis of the performance of heuristics on random and real-world social network data
None
Lab allocations have not been finalised