Lecture Notes in Computer Science
Refine
Year of publication
- 2015 (1) (remove)
Document Type
Language
- English (1)
Has Fulltext
- yes (1)
Is part of the Bibliography
- no (1)
Keywords
- Computerlinguistik (1)
- Food item (1)
- Grafische Darstellung (1)
- Graph cluster (1)
- Information Extraction (1)
- Lebensmittel (1)
- Maschinelles Lernen (1)
- Neighbour classifier (1)
- Relation extraction (1)
- Unconnected node (1)
Publisher
- Springer (1)
9103
We examine the combination of pattern-based and distributional similarity for the induction of semantic categories. Pattern-based methods are precise and sparse while distributional methods have a higher recall. Given these particular properties we use the prediction of distributional methods as a back-off to pattern-based similarity. Since our pattern-based approach is embedded into a semi-supervised graph clustering algorithm, we also examine how distributional information is best added to that classifier. Our experiments are carried out on 5 different food categorization tasks.