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Knowledge Discovery in Data with selected Java Open Source Software

Language EnglishEnglish
Book Paperback
Book Knowledge Discovery in Data with selected Java Open Source Software Carlos Rojas
Libristo code: 16455838
Publishers Grin Publishing, June 2017
Research Paper (postgraduate) from the year 2008 in the subject Computer Science - Applied, grade: 4... Full description
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Research Paper (postgraduate) from the year 2008 in the subject Computer Science - Applied, grade: 4.0, University of Louisville (Speed College of Engineering), language: English, abstract: 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.

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About the book

Full name Knowledge Discovery in Data with selected Java Open Source Software
Language English
Binding Book - Paperback
Date of issue 2017
Number of pages 20
EAN 9783668443112
ISBN 3668443114
Libristo code 16455838
Publishers Grin Publishing
Weight 54
Dimensions 178 x 254 x 1
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