VU AWM 2008

27.2.
Organisatorisches, Einführung in das Themenfeld (Markus Strohmaier & Michael Granitzer)

5.3.
Part-of-Speech Tagging und Language Modeling (Markus Strohmaier)

Einführende Literatur:
A simple rule-based part of speech tagger, E. Brill In Proceedings of the workshop on Speech and Natural Language, 1992

Themen: Word classes and POS tagging, Tagsets, Closed vs. Open classes, Corpora, Different types of POS tagger, POS tagging evaluation

12.3.
Information extraction (Thomas Neidhart)

Einführende Literatur:
* Automatic Information Extraction, H. Cunnigham, 2005, http://www.gate.ac.uk/sale/ell2/ie/
* An Overview and Classification of Adaptive Approaches to Information Extraction, Christian Siefkes and Peter Siniakov, 2005, http://www.siefkes.net/papers/overview-ie.pdf
* Introduction to Information Extraction Technology, Appelt, Douglas & David Israel, 1999, http://www.ai.sri.com/~appelt/ie-tutorial/

Themen:
Natural Language Processing, Machine learning methods for Language Processing, Extraction of (named) entities from text, Context sensitive entity extraction, Evaluation of Language Processing Systems, …

9.4.
Supervised Machine Learning (Mark Kröll)

Einführende Literatur:
“Introduction to IR” though a reference for information retrieval, chapters 13,14 and 15 cover major parts of this lecture; chapter 6 of Tom Mitchell’s ‘Machine Learning’ served as valuable resource for the Naive Bayes Classifier

Themen:
The talk gives an introduction to Supervised Machine Learning Techniques. The motivation should clarify the need and the application areas for supervised learning - also known as classification. Three popular classifiers are presented and explained in more detail - the Naive Bayes, the k-Nearest Neighbor and Support Vector Machines.

16.4.
Unsupervised Machine Learning (Michael Granitzer)

Einführende Literatur:
Berkhin, P. (2002). Survey Of Clustering Data Mining Techniques San Jose, CA: Accrue Software.(http://citeseer.ist.psu.edu/berkhin02survey.html)

Themen:
Clustering with focus on text collection, similarity & distance measures, memory and runtime complexities Algorithms: k-Means, Hierarchical Agglomerative Clustering (HAC), (Growing) Neural Gas Applications: topic extraction, document summarization, plagiarism analysis, search result clustering

23.4.
Information Retrieval (Michael Granitzer)

Einführende Literatur:
Chapters 4.1, 4.2, 5 in Fuhr, N. (2000). Information Retrieval - Skriptum zur Vorlesung im WS 00/01 Dortmund (http://www.is.inf.uni-due.de/courses/ir_ss06/index.html)

Themen:
Information Retrieval (IR) with focus on text retrieval, formal definition of IR, comparison to data retrieval, boolean and vector space retrieval, similarity search, relevance feedback, connection to information visualisation and unsupervised machine learning Applications: Internet vs. Enterprise vs. Desktop Search

30.4.
Paper / project presentations by students

7.5.
Paper / project presentations by students

14.5.
Graphen und Graphenalgorithmen (A. Juffinger)

Einführende Literatur:
R. Diestel: Graphentheorie. 3. Auflage. Springer, Heidelberg 2005. ISBN 3-540-67656-2, H.W. Hamacher and K. Klamroth: Lineare und Netzwerk-Optimierung. 1. Auflage. Springer. 2000, Journal of Graph Theory, L. R. Ford, D. R. Fulkerson: Flows in Networks, 1962

Themen:
Graph history, formal definition, storage of graphs and popular graph problems will be discussed in this lecture. Starting with Shortest Spanning Tree, Shortest Path and Matching problems we will dive into State of the Art Graph Problems in Modern Information Retrieval (Ontologies and Semantic Networks)

21.5.
Multimedia (M. Lux)

Einführende Literatur: TBA
Themen: TBA

28.5.
Information Visualization (V. Sabol)

Einführende Literatur:
* “Visualizing Knowledge Domains” by Katy Börner, Chaomei Chen, Kevin W. Boyack, 2003
(http://ella.slis.indiana.edu/~katy/paper/arist02.pdf)
* “Information Visualization: Perception for Design” by Colin Ware, 2nd edition, Morgan Kaufmann, 2004
* “The Visual Display of Quantitative Information” by Edward R. Tufte, 2nd edition, Graphics Press, 2001

Themen:
Definition of visualisation, data/information/knowledge visualisation, units of visual representation, interactivity, visual analytics and relation to knowledge discovery, technologies supporting visualisation, selected visualization examples and applications, usability engineering and evaluation

4.6.
Ontology-based Retrieval (P. Scheir)

Themen: Diese Vorlesungseinheit beschäftigt sich mit Ontologie-basiertem Information Retrieval und Information Retrieval im Semantic Web. Es werden Anwendungsfälle für Ontologie-basiertes Information Retrieval aufgezeigt. Es wird gezeigt, dass Suchansätze für das Semantic Web nicht zwingendermassen Ontologie-basiert sein müssen.
Im Kontext von Suche im Semantic Web wird auf das Spannungsfeld zwischen Data und Information Retrieval eingegangen.

11.6.
Service Oriented Architectures (W. Klieber)

Einführende Literatur:
SOA in the Real world, Microsoft 2007, Link; Douglas Foxvog, “Ontolizing ED: First Steps and Initial Experience”, IEEE, proceedingss, DEEC’05, Link; Dragos-Anton Manolescu, phd thesis 2000, http://micro-workflow.com/phdthesis/

Themen:
Starting with an introduction to services and (semantic) service oriented architectures, this lecture describes how to realize KD-projects by modelling KD-tasks as services and workflows.

18.6.
Project presentations by students

25.6.
Project presentations by students