Abstract : In the context of web-scale taxonomies such as Directory Mozilla(www.dmoz.org), previous works have shown the existence of power law distribution in the size of the categories for every level in the taxonomy. In this work, we analyse how such high-level semantics can be leveraged to evaluate accuracy of hierarchical classifiers which automati- cally assign the unseen documents to leaf-level categories. The proposed method offers computational advantages over k-fold cross-validation.
https://hal.archives-ouvertes.fr/hal-00944212 Contributor : Rohit BabbarConnect in order to contact the contributor Submitted on : Monday, February 10, 2014 - 12:50:32 PM Last modification on : Thursday, October 21, 2021 - 3:47:55 AM
Massih-Reza Amini, Rohit Babbar, Eric Gaussier, Ioannis Partalas. Comparative Classifier Evaluation for Web-scale Taxonomies using Power Law. The Semantic Web: ESWC 2013 Satellite Events, May 2013, France. pp.310-311. ⟨hal-00944212⟩