Development and support of student technology startups by creating a successful startup community; assistance in providing favorable conditions from external partners for investment and development of ideas.
The university’s project-based activities are aimed at implementing grant-based and commercial projects, as well as at enhancing the availability of education in IT areas.
Exploring dimension reduction techniques for text
Large multidimensional data sets are hard to visualize. Most existing methods dedicate visual space to multiple items or multiple features. In this work, we explore dimensionality reduction methods to capture both properties. We show that self-organizing maps (SOM) are the good choice for screen and paper visualization. We involve colors to make multiple texts comparable on a single image. We discuss important properties of our visualization method and propose an optimal parameter set with respect to text vocabulary size. Our methods are implemented in python programming language and are available as an open-source visualization library.