Dependency Detection in MobiMine and Random Matrices

This paper describes a novel approach to detect correlation from data streams in the context of MobiMine --- an experimental mobile data mining system. It presents a brief description of the MobiMine and identifies the problem of detecting dependencies among stocks from incrementally observed financial data streams. This is a non-trivial problem since the stock-market data is inherently noisy and small incremental volumes of data makes the estimation process more vulnerable to noise