LCN2 Seminar: Geometric Representations of Complementarity-Driven Networks
- Friday 25 March 2022
- Room 313
You can also attend via Zoom.Zoom link
52th LCN2 seminar
Speaker: Maksim Kitsak (TU Delft)
Title: Geometric Representations of Complementarity-Driven Networks.
Similarity is one of the key principles underlying the formation of social networks: the more similar individuals are the higher is the chance for a social interaction between them. Latent geometry provides an elegant way to model similarity in social networks. Network nodes are viewed as points in underlying latent or hidden space, such that distances between them quantify node similarities: the smaller the distance between the two nodes the more similar they are. It is the similarity interpretation of latent distances that lies at the origin of many applications of network embeddings, including link prediction, soft community detection and clustering, network navigation, and search.
In my talk, however, I will focus on another class of networks that are shaped not only by similarity but also by the complementarity principle. Examples of complementarity-driven networks include interdisciplinary collaboration networks, networks of interacting proteins, and, possibly, food webs. Indeed, individuals with complementary expertise are more likely to solve an interdisciplinary problem of interest, and interactions often take place between proteins with complementary chemical properties and/or complementary binding interfaces. One of the most popular food web network models, the niche model, is based not on the similarity but on the complementarity principle, as I will demonstrate.
In my talk, I will argue that existing network embedding methods are not readily applicable to complementarity-driven networks. I will then deduce a proper framework for the representations of complementarity-driven networks and demonstrate its efficiency in network reconstruction tasks.