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A Comparison of Approaches for Geospatial Entity Extraction from Wikipedia
Abstract We target in this paper the challenge of eWe target in this paper the challenge of extracting geospatial data from the article text of the English Wikipedia. We present the results of a Hidden Markov Model (HMM) based approach to identify location-related named entities in the our corpus of Wikipedia articles, which are primarily about battles and wars due to their high geospatial content. The HMM NER process drives a geocoding and resolution process, whose goal is to determine the correct coordinates for each place name (often referred to as grounding). We compare our results to a previously developed data structure and algorithm for disambiguating place names that can have multiple coordinates. We demonstrate an overall f-measure of 79.63% identifying and geocoding place names. Finally, we compare the results of the HMM-driven process to earlier work using a Support Vector Machine.rlier work using a Support Vector Machine.
Abstractsub We target in this paper the challenge of eWe target in this paper the challenge of extracting geospatial data from the article text of the English Wikipedia. We present the results of a Hidden Markov Model (HMM) based approach to identify location-related named entities in the our corpus of Wikipedia articles, which are primarily about battles and wars due to their high geospatial content. The HMM NER process drives a geocoding and resolution process, whose goal is to determine the correct coordinates for each place name (often referred to as grounding). We compare our results to a previously developed data structure and algorithm for disambiguating place names that can have multiple coordinates. We demonstrate an overall f-measure of 79.63% identifying and geocoding place names. Finally, we compare the results of the HMM-driven process to earlier work using a Support Vector Machine.rlier work using a Support Vector Machine.
Bibtextype inproceedings  +
Doi 10.1109/ICSC.2010.74  +
Has author Daryl Woodward + , Jeremy Witmer + , Jugal Kalita +
Has extra keyword Entity extractions + , F-measure + , Geo coding + , Geo-spatial + , Geo-spatial data + , Named entities + , Process drives + , Resolution process + , Wikipedia + , Data structures + , Hidden Markov models + , Semantics +
Isbn 9780769541549  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 402–407  +
Published in Proceedings - 2010 IEEE 4th International Conference on Semantic Computing, ICSC 2010 +
Title A comparison of approaches for geospatial entity extraction from Wikipedia +
Type conference paper  +
Year 2010 +
Creation dateThis property is a special property in this wiki. 6 November 2014 13:27:55  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 6 November 2014 13:27:55  +
redirect page A comparison of approaches for geospatial entity extraction from Wikipedia  +
DateThis property is a special property in this wiki. 2010  +
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