CS 6804 Natural Language Processing Techniques for Applications on Noisy Data Spring 2016 Alla Rozovskaya Today, a wealth of data is available at our fingertips that we would like to make use of to solve societal challenges in various domains. In the healthcare domain, for example, we have access to large data sets of electronic health records. In the educational domain, we have large repositories of data generated from educational software related to people's learning activities in educational settings. In the social media domain, there are a lot of things that can be studied. We can make predictions about disasters and epidemics; we can do sentiment and opinion mining. To make use of this unstructured data, however, we need NLP technology. Unfortunately, traditional NLP technology breaks down on this noisy data, because it is trained to deal with well-formed text. In this graduate seminar, we will read and discuss papers that are concerned with developing computational models to process noisy non-standard data. The students will also work on research projects to develop techniques and approaches in this area.