Altering document term vectors for classification: ontologies as expectations of co-occurrence

Meenakshi Nagarajan, Amit P. Sheth, Marcos Kawazoe Aguilera, Kimberly Keeton, Arif Merchant, Mustafa Uysal

Abstract: In this paper we extend the state-of-the-art in utilizing background knowledge for supervised classification by exploiting the semantic relationships between terms explicated in Ontologies. Preliminary evaluations indicate that the new approach generally improves precision and recall, more so for hard to classify cases and reveals patterns indicating the usefulness of such background knowledge.