Developing an Agent-Based Framework for Intelligent Geocoding
Geocoding is essential to translating a physical address such as a house, business or landmark into spatial coordinates which are used in a range of everyday activities. Geocoding is an active area of research, both within the literature and also in industry. Despite progress in the field, there remains a small portion of addresses which are difficult to geocode. The purpose of this research is to explore the use of agent-based techniques to add intelligence to the geocoding process. The importance of the research stems from its potential to move geocoding in a new direction, by complementing current theory and practice with control and knowledge improvements which will improve geocoding results. The investigation was undertaken by identifying the issues relevant to intelligent geocoding, designing an agentbased solution and building a prototype. The prototype was then evaluated using sample addresses to assess its quantitative performance, and its qualitative performance was evaluated based on the new functionality it provided. Results indicate that intelligence in geocoding is a product of both context and semantics (at a conceptual level) and control and knowledge (at an implementation level), where the two are “connected” by the agent paradigm which is both a representation and a solution. Other conclusions include that further development in learning and semantics in geocoding would allow the knowledge base to infer new knowledge and store insights regarding the spatial cognition of users.