SMU Assistant Professor of Information Systems Hady W. Lauw’s research on data mining tries to identify useful patterns from large amounts of information. Assistant Prof Lauw argues that with more people using online resources that generates more data, there needs to be a better way for researchers to sift through all the data and recommend more efficient ways to convert them into real-world results. His paper, Modelling Contextual Agreement in Preferences, is aimed at providing a more granular and targeted approach to product and service recommendations through a generative model he calls the Differential Probabilistic Matrix Factorization (DPMF). Another two of his papers focus on how the data mining techniques he has developed can be applied to the cable television industry. Assistant Prof Lauw said that data mining can help us to simplify the choice conundrum, and reduce our options to the one that matters the most.