Comparative study of clustering algorithms on textual databases
Clustering of curricula vitae into comptency-based groups to support knowledge management
(Sprache: Englisch)
The large collection of Brazilian researcher`s curricula vitae held on the Lattes Platform provides a formidable base for the discovery of information about people`s skills, abilities and knowledge which is referred to as competencies. Results from the...
Leider schon ausverkauft
versandkostenfrei
Buch
49.00 €
24 DeutschlandCard Punkte
sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
Produktdetails
Produktinformationen zu „Comparative study of clustering algorithms on textual databases “
The large collection of Brazilian researcher`s curricula vitae held on the Lattes Platform provides a formidable base for the discovery of information about people`s skills, abilities and knowledge which is referred to as competencies. Results from the analysis of competencies can be applied in human resources, project management and the planning of on-the-job training in terms of how to enforce collaboration, how to build or modify teams and how to direct resources. The study builds on Knowledge Discovery in Textual Database (KDT) in order to analyze each step from data selection, term extraction and weighting to clustering and the interpretation toward knowledge management. For the division of an input dataset into a priori unknown competency-based groups two clustering algorithms have been implemented, namely the k-means algorithm and Kohonen Self-Organizing Maps (Kohonen-SOM). Two illustration techniques for competency-based groups as well as decision rules for the application of both algorithms will be presented.
Klappentext zu „Comparative study of clustering algorithms on textual databases “
The large collection of Brazilian researcher`s curricula vitae held on the Lattes Platform provides a formidable base for the discovery of information about people`s skills, abilities and knowledge which is referred to as competencies. Results from the analysis of competencies can be applied in human resources, project management and the planning of on-the-job training in terms of how to enforce collaboration, how to build or modify teams and how to direct resources. The study builds on Knowledge Discovery in Textual Database (KDT) in order to analyze each step from data selection, term extraction and weighting to clustering and the interpretation toward knowledge management. For the division of an input dataset into a priori unknown competency-based groups two clustering algorithms have been implemented, namely the k-means algorithm and Kohonen Self-Organizing Maps (Kohonen-SOM). Two illustration techniques for competency-based groups as well as decision rules for the applicationof both algorithms will be presented.
Autoren-Porträt von Sebastian R. Spiegler
2007 - present PhD studies, Machine Learning, Computer Science Dept., University of Bristol, UK 2004 - 2007 Computer science and information systems, Federal University of Santa Catarina, Brazil 2000 - 2007 Diploma. Computer science and business administration, Technical University Ilmenau, Germany
Bibliographische Angaben
- Autor: Sebastian R. Spiegler
- 2008, 96 Seiten, Maße: 17 x 24 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag Dr. Müller
- ISBN-10: 3836448793
- ISBN-13: 9783836448796
Sprache:
Englisch
Kommentar zu "Comparative study of clustering algorithms on textual databases"
0 Gebrauchte Artikel zu „Comparative study of clustering algorithms on textual databases“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Comparative study of clustering algorithms on textual databases".
Kommentar verfassen