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--- data:concrete_nouns_categorization [2008/01/19 17:09]
alexlenci
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-====== Task 1a: Concrete Nouns Categorization ======
-==== Introduction ====
-The goal of the sub-task is to group concrete nouns into semantic categories.
-The {{concnouns.categorization.dataset.tar.gz |data set}} consists of 44 concrete nouns, belonging to 7 semantic categories (four animates and two inanimates). All the nouns are included in the feature norms described in McRae et al. (2005) (cf. [[comparison_with_speaker-generated_features|Task3]]).
-==== Task Operationalization ====
-We operationalize the concrete noun categorization as a clustering task. Since the data set is organized hierarchically,
-we perform different leves of clustering, to test the model with different number of classes, differenring also for their level of generality:
-  * 7-way clustering - the model will be tested with respet to its abilityt to cluters the data at the highest levels of granularity. The 7 classes are: bird (peacock), groundAnimal (lion), fruitTree (cherry), green (potato), kitchenware (spoon), instrument (hammer), vehicle (car);
-  * 4-way clustering - the model will be tested with respet to its abilityt to cluster the data in to 4 classes: animal (superordinate of bird and groundanimal), vegetable (superordinate of fruitTree and green), tool (superordinate of kitchenware and instrument), vehicle;
-  * 2-way clustering -
-Back to [[Start]]