Article

Free access

Location normalization for information extraction

Authors:

Huifeng Li,

Rohini K. Srihari,

Cheng Niu,

Wei LiAuthors Info & Claims

COLING '02: Proceedings of the 19th international conference on Computational linguistics - Volume 1

Pages 1 - 7

https://doi.org/10.3115/1072228.1072355

Published: 24 August 2002 Publication History

PDF eReader

Abstract

Ambiguity is very high for location names. For example, there are 23 cities named 'Buffalo' in the U.S. Country names such as 'Canada', 'Brazil' and 'China' are also city names in the USA. Almost every city has a Main Street or Broadway. Such ambiguity needs to be handled before we can refer to location names for visualization of related extracted events. This paper presents a hybrid approach for location normalization which combines (i) lexical grammar driven by local context constraints, (ii) graph search for maximum spanning tree and (iii) integration of semi-automatically derived default senses. The focus is on resolving ambiguities for the following types of location names: island, town, city, province, and country. The results are promising with 93.8% accuracy on our test collections.

References

[1]

Cormen, Thomas H., Charles E. Leiserson, and Ronald L. Rivest. 1990. Introduction to Algorithm. The MIT Press, pp. 504--505.

Digital Library

Google Scholar

[2]

Dagon, Ido and Alon Itai. 1994. Word Sense Disambiguation Using a Second Language Monolingual Corpus. Computational Linguistics, Vol. 20, pp. 563--596.

Digital Library

Google Scholar

[3]

Gale, W. A., K. W. Church, and D. Yarowsky. 1992. One Sense Per Discourse. In Proceedings of the 4th DARPA Speech and Natural Language Workshop. pp. 233--237.

Digital Library

Google Scholar

[4]

Hirst, Graeme. 1987. Semantic Interpretation and the Resolution of Ambiguity. Cambridge University Press, Cambridge.

Digital Library

Google Scholar

[5]

Krupka, G. R. and K. Hausman. 1998. IsoQuest Inc.: Description of the NetOwl (TM) Extractor System as Used for MUC-7. Proceedings of MUC.

Google Scholar

[6]

McRoy, Susan W. 1992. Using Multiple Knowledge Sources for Word Sense Discrimination. Computational Linguistics, 18(1): 1--30.

Digital Library

Google Scholar

[7]

Ng, Hwee Tou and Hian Beng Lee. 1996. Integrating Multiple Knowledge Sources to Disambiguate Word Sense: an Exemplar-based Approach. In Proceedings of 34th Annual Meeting of the Association for Computational Linguistics, pp. 40--47, California.

Digital Library

Google Scholar

[8]

Srihari, Rohini, Cheng Niu, and Wei Li. 2000. A Hybrid Approach for Named Entity and Sub-Type Tagging. In Proceedings of ANLP 2000, Seattle.

Digital Library

Google Scholar

[9]

Yarowsky, David. 1992. Word-sense Disambiguation Using Statistical Models of Roget's Categories Trained on Large Corpora. In Proceedings of the 14th International Conference on Computational Linguistics (COLING-92), pp. 454--460, Nates, France.

Digital Library

Google Scholar

[10]

Yarowsky, David. 1995. Unsupervised Word Sense Disambiguation Rivaling Supervised Methods. In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics, Cambridge, Massachusetts.

Digital Library

Google Scholar

Cited By

View all

Monteiro BDavis CFonseca F(2016)A survey on the geographic scope of textual documentsComputers & Geosciences10.1016/j.cageo.2016.07.01796:C(23-34)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.cageo.2016.07.017
Ji RGao YLiu WXie XTian QLi X(2015)When Location Meets Social MultimediaACM Transactions on Intelligent Systems and Technology10.1145/25971816:1(1-18)Online publication date: 26-Mar-2015
https://dl.acm.org/doi/10.1145/2597181
Liu FVasardani MBaldwin TAhlers DWilde EMartins B(2014)Automatic Identification of Locative Expressions from Social Media TextProceedings of the 4th International Workshop on Location and the Web10.1145/2663713.2664426(9-16)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2663713.2664426
Show More Cited By

Location normalization for information extraction
1. Hardware
  1. Power and energy
    1. Power estimation and optimization

Recommendations

Location Extraction from Social Media: Geoparsing, Location Disambiguation, and Geotagging

Location extraction, also called “toponym extraction,” is a field covering geoparsing, extracting spatial representations from location mentions in text, and geotagging, assigning spatial coordinates to content items. This article evaluates five “best-...
Learning for information extraction: from named entity recognition and disambiguation to relation extraction
Optimizing information extraction programs over evolving text

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

COLING '02: Proceedings of the 19th international conference on Computational linguistics - Volume 1

August 2002

1184 pages

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 24 August 2002

Qualifiers

Article

Acceptance Rates

Overall Acceptance Rate 1,537 of 1,537 submissions, 100%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

28
Total Citations
View Citations
603
Total Downloads

Downloads (Last 12 months)86
Downloads (Last 6 weeks)12

Reflects downloads up to 22 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Monteiro BDavis CFonseca F(2016)A survey on the geographic scope of textual documentsComputers & Geosciences10.1016/j.cageo.2016.07.01796:C(23-34)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.cageo.2016.07.017
Ji RGao YLiu WXie XTian QLi X(2015)When Location Meets Social MultimediaACM Transactions on Intelligent Systems and Technology10.1145/25971816:1(1-18)Online publication date: 26-Mar-2015
https://dl.acm.org/doi/10.1145/2597181
Liu FVasardani MBaldwin TAhlers DWilde EMartins B(2014)Automatic Identification of Locative Expressions from Social Media TextProceedings of the 4th International Workshop on Location and the Web10.1145/2663713.2664426(9-16)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2663713.2664426
Choi SSong HPark SLee S(2014)A POI Categorization by Composition of Onomastic and Contextual InformationProceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) - Volume 0210.1109/WI-IAT.2014.78(38-45)Online publication date: 11-Aug-2014
https://dl.acm.org/doi/10.1109/WI-IAT.2014.78
Garrido ABuey MIlarri SMena E(2013)GEO-NASSProceedings of the 17th East European Conference on Advances in Databases and Information Systems - Volume 813310.1007/978-3-642-40683-6_5(56-69)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1007/978-3-642-40683-6_5
Liu XZhou MWei FFu ZZhou XLi HLin COsborne M(2012)Joint inference of named entity recognition and normalization for tweetsProceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 110.5555/2390524.2390598(526-535)Online publication date: 8-Jul-2012
https://dl.acm.org/doi/10.5555/2390524.2390598
Strötgen JGertz MBoughida KHoward BNelson MVan de Sompel HSølvberg I(2012)Event-centric search and exploration in document collectionsProceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries10.1145/2232817.2232859(223-232)Online publication date: 10-Jun-2012
https://dl.acm.org/doi/10.1145/2232817.2232859
Qin TXiao RFang LXie XZhang LAgrawal DZhang PAbbadi AMokbel M(2010)An efficient location extraction algorithm by leveraging web contextual informationProceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/1869790.1869801(53-60)Online publication date: 2-Nov-2010
https://dl.acm.org/doi/10.1145/1869790.1869801
Strötgen JGertz MPopov PPurves RClough PJones C(2010)Extraction and exploration of spatio-temporal information in documentsProceedings of the 6th Workshop on Geographic Information Retrieval10.1145/1722080.1722101(1-8)Online publication date: 18-Feb-2010
https://dl.acm.org/doi/10.1145/1722080.1722101
Abrol SKhan LPurves RClough PJones C(2010)TWinnerProceedings of the 6th Workshop on Geographic Information Retrieval10.1145/1722080.1722093(1-8)Online publication date: 18-Feb-2010
https://dl.acm.org/doi/10.1145/1722080.1722093
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Abstract

References

Cited By

Recommendations

Location Extraction from Social Media: Geoparsing, Location Disambiguation, and Geotagging

Learning for information extraction: from named entity recognition and disambiguation to relation extraction

Optimizing information extraction programs over evolving text

Comments

Information

Published In

Publisher

Publication History

Qualifiers

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

PDF

eReader

Login options

Full Access

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations