Mixing Semantic Networks and Conceptual Vectors: The Case of Hyperonymy

In this paper, we focus on lexical semantics, a key issue in Natural Language Processing (NLP) that tends to converge with conceptual Knowledge Representation (KR) and ontologies. When ontological representation is needed, hyperonymy, the closest approximation to the is-a relation, is at stake. In this paper we describe the principles of our vector model (CVM: Conceptual Vector Model), and show how to account for hyperonymy within the vector-based frame for semantics. We show how hyperonymy diverges from is-a and what measures are more accurate for hyperonymy representation. Our demonstration results in initiating a ’cooperation’ process between semantic networks and conceptual vectors. Text automatic rewriting or enhancing, ontology mapping with natural language expressions, are examples of applications that can be derived from the functions we

• Type: Conference
• Year: 2003
• Where: IEEEICCI
• Authors: Violaine Prince, Mathieu Lafourcade
• Keywords: Conceptual Vectors, IEEEICCI 2003, Informatics, Natural Language, Vector Model