Knowledge Discovery in Data with Selected Java Open Source SoftwareCIML: Machine Learning Virtual Organizations, Computational Intelligence and Machine Learning (2008)
We give an overview of our experience in utilizing several open source packages and composing them into sophisticated applications to solve several challenging problems as part of some of the research projects at the Knowledge Discovery & Web Mining lab at the Universe of Louisville. The projects have a common theme of knowledge discovery, however their application domains span a variety of areas. These areas range from mining Web data streams to mining Astronomy related image data, as well as Web information retrieval in social multimedia websites and e-learning platforms. As is already known, a significant proportion of the effort in any real life project involving knowledge discovery in data (KDD) is devoted to the early and final stages of KDD, i.e., the data collection and preprocessing, and the visualization of the results. Given the nature of the data in our projects, we expose our experience in handling text data and image data as part of the KDD process. In addition to the open source packages that we used, we will briefly present some of the stand-alone software that we developed in the lab, in particular a suite of software for clustering and for stream data mining.
- stream clustering techniques,
Citation InformationLeyla Zhuhadar, Carlos Rojas, Olfa Nasraoui, Nurcan Durak, et al.. "Knowledge Discovery in Data with Selected Java Open Source Software" CIML: Machine Learning Virtual Organizations, Computational Intelligence and Machine Learning (2008)
Available at: http://works.bepress.com/leyla-zhuhadar/13/