Poster Title:

Altering Document Term Vectors for Classification - Ontologies as Expectations of Co-occurrence

Authors:

• Meenakshi Nagarajan (Kno.e.sis Center, Wright State University)
• Amit Sheth (Kno.e.sis Center, Wright State University)
• Marcos Aguilera (HP Labs, Palo Alto, CA)
• Kimberly Keeton (HP Labs, Palo Alto, CA)
• Arif Merchant (HP Labs, Palo Alto, CA)
• Mustafa Uysal (HP Labs, Palo Alto, CA)

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 and reveals patterns indicating the usefulness of such background knowledge.