100,43 €
111,59 €
-10% with code: EXTRA
Knowledge Discovery in Data with selected Java Open Source Software
Knowledge Discovery in Data with selected Java Open Source Software
100,43
111,59 €
  • We will send in 10–14 business days.
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 comm…
111.59
  • Publisher:
  • ISBN-10: 3668443114
  • ISBN-13: 9783668443112
  • Format: 21 x 29.7 x 0.1 cm, minkšti viršeliai
  • Language: English
  • SAVE -10% with code: EXTRA

Knowledge Discovery in Data with selected Java Open Source Software (e-book) (used book) | bookbook.eu

Reviews

Description

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.

EXTRA 10 % discount with code: EXTRA

100,43
111,59 €
We will send in 10–14 business days.

The promotion ends in 23d.03:21:50

The discount code is valid when purchasing from 10 €. Discounts do not stack.

Log in and for this item
you will receive 1,12 Book Euros!?
  • Author: et al
  • Publisher:
  • ISBN-10: 3668443114
  • ISBN-13: 9783668443112
  • Format: 21 x 29.7 x 0.1 cm, minkšti viršeliai
  • Language: English English

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.

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)