Exploring Creative Concepts in the Nearest Neighborhood using Lexical Ontologies Prasad Pingali 1 , J Jagadeesh 1 , Vasudeva Varma 1 , Bipin Indurkhya 1 , 1 LTRC, International Institute of Information Technology, Hyderabad, India [pvvpr, j_jagdeesh, vv, bipin]@iiit.ac.in Abstract. Conceptual blending is an important area of research for creativity modeling. In this paper we present a creativity model that takes an existing blend and generates new blends using the nearest neighborhood replacements from a lexical ontology. For example “Artificial Intelligence” is a compounded concept comprising of “Artificiality” and “Intelligence” as two sub-concepts. After concept generation, the system comes up with “Artificial Creativity” as one of the generated concepts. This project is part of a larger ongoing project called CAPRICON whose goal is to provide with stimuli for new futuristic concepts. This tool is a creativity enhancement tool that helps users enhance their creative thinking by providing stimuli for new concepts. 1 Introduction The model presented in this paper is part of a larger ongoing project codenamed CAPRICON. The goal of CAPRICON is to be able to predict futuristic concepts and ideas using the already known concepts. This project is based on the conceptual blending theory. Conceptual Blending is a theory of cognition. According to the theory of Conceptual Blending, elements and vital relations from diverse scenarios are "blended" in a subconscious process. This process is known as Conceptual Blending, and is assumed to be ubiquitous to everyday thought and language. Insights obtained from these blends constitute the products of creative thinking. Gilles Fauconnier and Mark Turner developed the theory of Conceptual Blending. This theory is based on basic ideas advanced by George Lakoff [7]. Generating conceptual blends is a challenging problem in computational creativity. Discussed at length in Fauconnier and Turner [3] and Coulson [2], conceptual blending is a theoretical framework for exploring human information integration. It involves a set of operations for combining dynamic cognitive models in a network of "mental spaces", or partitions or speakers' referential representations. Fauconnier and Turner [3] suggest that a small set of partially compositional processes operate in the creative construction of meaning in analogy, metaphor, counterfactuals, concept combination, and even the comprehension of grammatical constructions. Blending processes depend centrally on projection mapping and dynamic simulation to develop