ESCHER: Efficient and Scalable Hypergraph Evolution Representation with Application to Triad Counting

This article introduces ESCHER, a new method for representing and analyzing evolving hypergraphs. The focus is on efficiency and scalability, particularly in the context of triad counting. The use of hypergraphs suggests a complex data structure, and the emphasis on scalability implies the method is designed for large datasets. The application to triad counting is a specific use case, likely demonstrating the practical utility of ESCHER.

• •ESCHER is a new method for representing and analyzing evolving hypergraphs.
• •The method prioritizes efficiency and scalability.
• •The application to triad counting demonstrates practical utility.
• •The research likely targets large datasets.