  One way to study an hypergraph is to attach to it a tensor. Tensors are a
generalization of matrices, and they are an efficient way to encode information
in a compact form. In this paper we study how properties of weighted
hypergraphs are reflected on eigenvalues and eigenvectors of their associated
tensors. We also show how to efficiently compute eingenvalues with some
techniques from numerical algebraic geometry.
