An Axiomatic Approach to Link Prediction

Link prediction functions are important tools that are used to predict the evolution of a network, to locate hidden or surprising links, and to recommend new connections that should be formed. Multiple link prediction functions have been developed in the past. However, their evaluation has mostly been based on experimental work, which has shown that the quality of a link prediction function varies significantly depending on the input domain. There is currently very little understanding of why and how a specific link prediction function works well for a particular domain. The underlying foundations of a link prediction function are often left informal—each function contains implicit assumptions about the dynamics of link formation, and about structural properties that result from these dynamics. We draw upon the motivation used in characterizations of ranking algorithms, as well as other celebrated results from social choice, and present an axiomatic basis for link prediction. This...

• Type: Journal
• Year: 2015
• Where: AAAI
• Authors: Sara Cohen, Aviv Zohar
• Keywords: AAAI 2015, Intelligent Agents