Abstract
It is estimated that between 80% and 90% of governmental data collections contain address information. Geocoding – the process of assigning geographic coordinates to addresses – is becoming increasingly important in application areas that involve the analysis and mining of such data. In many cases, address records are captured and/or stored in a free-form or inconsistent manner. This fact complicates the task of accurately matching such addresses to spatially-annotated reference data. In this paper we describe a geocoding system that is based on a comprehensive high-quality geocoded national address database. It uses a learning address parser based on hidden Markov models to segment free-form addresses into components, and a rule-based matching engine to determine the best matches to the reference database.
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Christen, P., Willmore, A., Churches, T. (2006). A Probabilistic Geocoding System Utilising a Parcel Based Address File. In: Williams, G.J., Simoff, S.J. (eds) Data Mining. Lecture Notes in Computer Science(), vol 3755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11677437_11
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DOI: https://doi.org/10.1007/11677437_11
Publisher Name: Springer, Berlin, Heidelberg
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