A probabilistic geocoding system utilising a parcel based address file

Peter Christen; Alan Willmore; Tim Churches

doi:10.1007/11677437_11

A probabilistic geocoding system utilising a parcel based address file

Peter Christen^*, Alan Willmore, Tim Churches

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

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.

Original language	English
Title of host publication	Data Mining
Subtitle of host publication	Theory, Methodology, Techniques, and Applications
Publisher	Springer Verlag
Pages	130-145
Number of pages	16
ISBN (Print)	3540325476, 9783540325475
DOIs	https://doi.org/10.1007/11677437_11
Publication status	Published - 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3755 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/11677437_11

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Christen, P., Willmore, A., & Churches, T. (2006). A probabilistic geocoding system utilising a parcel based address file. In Data Mining: Theory, Methodology, Techniques, and Applications (pp. 130-145). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3755 LNAI). Springer Verlag. https://doi.org/10.1007/11677437_11

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title = "A probabilistic geocoding system utilising a parcel based address file",

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 Data Mining: Theory, Methodology, Techniques, and Applications. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3755 LNAI, Springer Verlag, pp. 130-145. https://doi.org/10.1007/11677437_11

A probabilistic geocoding system utilising a parcel based address file. / Christen, Peter; Willmore, Alan; Churches, Tim.
Data Mining: Theory, Methodology, Techniques, and Applications. Springer Verlag, 2006. p. 130-145 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3755 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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. A probabilistic geocoding system utilising a parcel based address file. In Data Mining: Theory, Methodology, Techniques, and Applications. Springer Verlag. 2006. p. 130-145. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11677437_11

A probabilistic geocoding system utilising a parcel based address file

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