Open Peer Review. Open Publishing. Open Access. Open Discussion. Open Directory. Open Recommendations. Open API. Open Source.
Classifying Entities into an Incomplete Ontology
Bhavana Dalvi, William W. Cohen, Jamie Callan
Jun 29, 2013 (modified: Jun 29, 2013)AKBC 2013 submissionreaders: everyone
Abstract:Exponential growth of unlabeled web-scale datasets, and class hierarchies to represent them, has given rise to new challenges for hierarchical classification. It is costly and time consuming to create a complete ontology of classes to represent entities on the Web. Hence, there is a need for techniques that can do hierarchical classification of entities into incomplete ontologies. In this paper we present Hierarchical Exploratory EM algorithm (an extension of the Exploratory EM algorithm) that takes a seed class hierarchy and seed class instances as input. Our method classifies relevant entities into some of the classes from the seed hierarchy
and on its way adds newly discovered classes into the hierarchy. Experiments with subsets of the NELL ontology and text datasets derived from the ClueWeb09 corpus show that our Hierarchical Exploratory EM approach improves seed class F1 by up to 21% when compared to its semi-supervised counterpart.
Enter your feedback below and we'll get back to you as soon as possible.