Mathematical Symbol Indexing for Digital Libraries

In this paper we describe our recent research for mathematical symbol indexing and its possible application in the Digital Library domain. The proposed approach represents mathematical symbols by means of Shape Contexts (SC) description. Indexed symbols are represented with a vector space-based method, but peculiar to our approach is the use of Self Organizing Maps (SOM) to perform the clustering instead of the commonly used k-means algorithm. The retrieval performance are measured on a large collection of mathematical symbols gathered from the widely used INFTY database.