10.5281/zenodo.1161505
https://zenodo.org/records/1161505
oai:zenodo.org:1161505
Ustalov, Dmitry
Dmitry
Ustalov
0000-0002-9979-2188
University of Mannheim
Graph Clustering for Natural Language Processing
Zenodo
2018
tutorial
clustering
graph theory
evaluation
natural language processing
2018-10-19
eng
Presentation
10.18653/v1/P17-1145
10.1007/978-3-642-25923-4
978-0-521-89613-9
10.1007/978-3-030-01204-5
https://github.com/nlpub/watset-java
urn:nbn:de:bsz:180-madoc-465240
10.18653/v1/P18-2010
10.1162/COLI_a_00354
10.5281/zenodo.3510160
10.5281/zenodo.4291121
10.5281/zenodo.1161504
https://zenodo.org/communities/natural-language-processing
ainl2018
Creative Commons Attribution Non Commercial Share Alike 4.0 International
Graph-based representations are proven to be an effective approach for a variety of Natural Language Processing (NLP) tasks. Graph clustering makes it possible to extract useful knowledge by exploiting the implicit structure of the data. In this tutorial, we will present several efficient graph clustering algorithms, show their strengths and weaknesses as well as their implementations and applications. Then, the evaluation methodology in unsupervised NLP tasks will be discussed.
These materials are published under a CC BY-NC-SA license. Please feel welcome to share them! For viewer convenience, the slides published on Zenodo do not include interactive step-by-step examples.