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In the [[semantic web]] era, a growing number of communities and networked enterprises started to access and interoperate through the [[internet]]. Modeling these communities and their information needs is important for several [[web application]]s, like topic-driven [[web crawler]]s,<ref>Menczer F., Pant G. and Srinivasan P. [http://citeseer.ist.psu.edu/menczer02topicdriven.html Topic-Driven Crawlers: machine learning issues].</ref> [[web service]]s,<ref>Fan J. and Kambhampati S. [http://portal.acm.org/citation.cfm?id=1058150.1058156 A Snapshot of Public Web Services], in ACM SIGMOD Record archive Volume 34 , Issue 1 (March 2005).</ref> [[Recommendation system|recommender systems]],<ref>Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings. [http://portal.acm.org/citation.cfm?id=1080344&dl=ACM&coll=&CFID=15151515&CFTOKEN=6184618 A market-based approach to recommender systems], in ACM Transactions on Information Systems (TOIS), 23(3), 2005.</ref> etc. The development of terminology extraction is essential to the [[language industry]].
In the [[semantic web]] era, a growing number of communities and networked enterprises started to access and interoperate through the [[internet]]. Modeling these communities and their information needs is important for several [[web application]]s, like topic-driven [[web crawler]]s,<ref>Menczer F., Pant G. and Srinivasan P. [http://citeseer.ist.psu.edu/menczer02topicdriven.html Topic-Driven Crawlers: machine learning issues].</ref> [[web service]]s,<ref>Fan J. and Kambhampati S. [http://portal.acm.org/citation.cfm?id=1058150.1058156 A Snapshot of Public Web Services], in ACM SIGMOD Record archive Volume 34 , Issue 1 (March 2005).</ref> [[Recommendation system|recommender systems]],<ref>Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings. [http://portal.acm.org/citation.cfm?id=1080344&dl=ACM&coll=&CFID=15151515&CFTOKEN=6184618 A market-based approach to recommender systems], in ACM Transactions on Information Systems (TOIS), 23(3), 2005.</ref> etc. The development of terminology extraction is essential to the [[language industry]].


One of the first steps to model the [[Domain knowledge|knowledge domain]] of a [[virtual community]] is to collect a vocabulary of domain-relevant terms, constituting the linguistic surface manifestation of domain [[Ontology_%28computer_science%29#Classes_.28concepts.29|concepts]]. Several methods to automatically extract technical terms from domain-specific document [[warehouse]]s have been described in the literature.<ref>Bourigault D. and Jacquemin C. [http://acl.ldc.upenn.edu/E/E99/E99-1003.pdf Term Extraction+Term Clustering: an integrated platform for computer-aided terminology], in Proc. of EACL, 1999.</ref><ref>{{cite journal|last1=Collier|first1=N.|last2=Nobata|first2=C.|last3=Tsujii|first3=J.|title=Automatic acquisition and classification of terminology using a tagged corpus in the molecular biology domain|journal=Terminology|volume=7|issue=2|pages=239-257|year=2002|doi=10.1075/term.7.2.07col}}</ref><ref>K. Frantzi, S. Ananiadou and H. Mima. (2000). [http://arnetminer.org/viewpub.do?pid=986374 Automatic recognition of multi-word terms: the C-value/NC-value method.] In: C. Nikolau and C. Stephanidis (Eds.) International Journal on Digital Libraries, Vol. 3, No. 2., pp. 115-130.</ref><ref>K. Frantzi, S. Ananiadou and J. Tsujii. (1998) [http://dl.acm.org/citation.cfm?id=696825 The C-value/NC-value Method of Automatic Recognition of Multi-word Terms], In: ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries, pp. 585-604. [isbn: 3-540-65101-2]</ref><ref>{{cite journal|author=L. Kozakov, Y. Park, T. Fin, Y. Drissi, Y. Doganata, and T. Cofino.|url=http://www.research.ibm.com/people/y/yurdaer/papers/ibmsysjournal2004a.pdf|title=Glossary extraction and utilization in the information search and delivery system for IBM Technical Support|journal=IBM System Journal|volume=43|issue=3|year=2004}}</ref><ref>Navigli R. and Velardi, P. [http://portal.acm.org/citation.cfm?id=1105712 Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites]. Computational Linguistics. 30 (2), MIT Press, 2004, pp. 151-179</ref><ref>Y. Park, R. J. Byrd, B. Boguraev. [http://portal.acm.org/citation.cfm?id=1072370&dl=ACM&coll=&CFID=15151515&CFTOKEN=6184618 "Automatic glossary extraction: beyond terminology identification"], International Conference On Computational Linguistics, Proceedings of the 19th international conference on Computational linguistics - Taipei, Taiwan, 2002.</ref><ref>[http://lcl2.di.uniroma1.it/~sclano Sclano, F.] and [http://www.dsi.uniroma1.it/~velardi/welcome.htm Velardi, P.]. [http://lcl2.di.uniroma1.it/termextractor TermExtractor]: a Web Application to Learn the Shared Terminology of Emergent Web Communities. To appear in Proc. of the 3rd International Conference on Interoperability for Enterprise Software and Applications (I-ESA 2007). Funchal (Madeira Island), Portugal, March 28–30th, 2007.</ref><ref>P. Velardi, R. Navigli, P. D'Amadio. [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4629722 Mining the Web to Create Specialized Glossaries], IEEE Intelligent Systems, 23(5), IEEE Press, 2008, pp. 18-25.</ref><ref>Wermter J. and Hahn U. [http://portal.acm.org/citation.cfm?id=1088648 Finding New terminology in Very large Corpora], in Proc. of K-CAP'05, October 2–5, 2005, Banff, Alberta, Canada</ref><ref>Wong, W., Liu, W. & Bennamoun, M. (2007) [http://portal.acm.org/citation.cfm?id=1378245.1378253 Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency]. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast. [isbn: 978-1-920682-51-4]</ref><ref>Wong, W., Liu, W. & Bennamoun, M. (2007) [http://portal.acm.org/citation.cfm?id=1378254&jmp=cit&coll=GUIDE&dl=GUIDE Determining Termhood for Learning Domain Ontologies in a Probabilistic Framework]. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast. [isbn: 978-1-920682-51-4]</ref><ref>{{cite book|author=Wong, W., Liu, W. & Bennamoun, M.|year=2008|doi=10.4018/978-1-59904-990-8|url=http://www.igi-global.com/reference/details.asp?ID=8224&v=tableOfContents|chapter=Determination of Unithood and Termhood for Term Recognition|editor=M. Song and Y. Wu|title=Handbook of Research on Text and Web Mining Technologies|publisher=IGI Global|isbn=978-1-59904-990-8}}</ref>
One of the first steps to model the [[Domain knowledge|knowledge domain]] of a [[virtual community]] is to collect a vocabulary of domain-relevant terms, constituting the linguistic surface manifestation of domain [[Ontology_%28computer_science%29#Classes_.28concepts.29|concepts]]. Several methods to automatically extract technical terms from domain-specific document warehouses have been described in the literature.<ref>Bourigault D. and Jacquemin C. [http://acl.ldc.upenn.edu/E/E99/E99-1003.pdf Term Extraction+Term Clustering: an integrated platform for computer-aided terminology], in Proc. of EACL, 1999.</ref><ref>{{cite journal|last1=Collier|first1=N.|last2=Nobata|first2=C.|last3=Tsujii|first3=J.|title=Automatic acquisition and classification of terminology using a tagged corpus in the molecular biology domain|journal=Terminology|volume=7|issue=2|pages=239-257|year=2002|doi=10.1075/term.7.2.07col}}</ref><ref>K. Frantzi, S. Ananiadou and H. Mima. (2000). [http://arnetminer.org/viewpub.do?pid=986374 Automatic recognition of multi-word terms: the C-value/NC-value method.] In: C. Nikolau and C. Stephanidis (Eds.) International Journal on Digital Libraries, Vol. 3, No. 2., pp. 115-130.</ref><ref>K. Frantzi, S. Ananiadou and J. Tsujii. (1998) [http://dl.acm.org/citation.cfm?id=696825 The C-value/NC-value Method of Automatic Recognition of Multi-word Terms], In: ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries, pp. 585-604. [isbn: 3-540-65101-2]</ref><ref>{{cite journal|author=L. Kozakov, Y. Park, T. Fin, Y. Drissi, Y. Doganata, and T. Cofino.|url=http://www.research.ibm.com/people/y/yurdaer/papers/ibmsysjournal2004a.pdf|title=Glossary extraction and utilization in the information search and delivery system for IBM Technical Support|journal=IBM System Journal|volume=43|issue=3|year=2004}}</ref><ref>Navigli R. and Velardi, P. [http://portal.acm.org/citation.cfm?id=1105712 Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites]. Computational Linguistics. 30 (2), MIT Press, 2004, pp. 151-179</ref><ref>Y. Park, R. J. Byrd, B. Boguraev. [http://portal.acm.org/citation.cfm?id=1072370&dl=ACM&coll=&CFID=15151515&CFTOKEN=6184618 "Automatic glossary extraction: beyond terminology identification"], International Conference On Computational Linguistics, Proceedings of the 19th international conference on Computational linguistics - Taipei, Taiwan, 2002.</ref><ref>[http://lcl2.di.uniroma1.it/~sclano Sclano, F.] and [http://www.dsi.uniroma1.it/~velardi/welcome.htm Velardi, P.]. [http://lcl2.di.uniroma1.it/termextractor TermExtractor]: a Web Application to Learn the Shared Terminology of Emergent Web Communities. To appear in Proc. of the 3rd International Conference on Interoperability for Enterprise Software and Applications (I-ESA 2007). Funchal (Madeira Island), Portugal, March 28–30th, 2007.</ref><ref>P. Velardi, R. Navigli, P. D'Amadio. [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4629722 Mining the Web to Create Specialized Glossaries], IEEE Intelligent Systems, 23(5), IEEE Press, 2008, pp. 18-25.</ref><ref>Wermter J. and Hahn U. [http://portal.acm.org/citation.cfm?id=1088648 Finding New terminology in Very large Corpora], in Proc. of K-CAP'05, October 2–5, 2005, Banff, Alberta, Canada</ref><ref>Wong, W., Liu, W. & Bennamoun, M. (2007) [http://portal.acm.org/citation.cfm?id=1378245.1378253 Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency]. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast. [isbn: 978-1-920682-51-4]</ref><ref>Wong, W., Liu, W. & Bennamoun, M. (2007) [http://portal.acm.org/citation.cfm?id=1378254&jmp=cit&coll=GUIDE&dl=GUIDE Determining Termhood for Learning Domain Ontologies in a Probabilistic Framework]. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast. [isbn: 978-1-920682-51-4]</ref><ref>{{cite book|author=Wong, W., Liu, W. & Bennamoun, M.|year=2008|doi=10.4018/978-1-59904-990-8|url=http://www.igi-global.com/reference/details.asp?ID=8224&v=tableOfContents|chapter=Determination of Unithood and Termhood for Term Recognition|editor=M. Song and Y. Wu|title=Handbook of Research on Text and Web Mining Technologies|publisher=IGI Global|isbn=978-1-59904-990-8}}</ref>


Typically, approaches to automatic term extraction make use of linguistic processors ([[part of speech tagging]], [[phrase chunking]]) to extract terminological candidates, i.e. syntactically plausible terminological [[noun phrase]]s, NPs (e.g. compounds "credit card", adjective-NPs "local tourist information office", and prepositional-NPs "board of directors" - in English, the first two constructs are the most frequent). Terminological entries are then filtered from the candidate list using statistical and [[machine learning]] methods. Once filtered, because of their low ambiguity and high specificity, these terms are particularly useful for conceptualizing a [[Domain knowledge|knowledge domain]] or for supporting the creation of a [[Ontology_%28computer_science%29#Domain_ontologies_and_upper_ontologies|domain ontology]]. Furthermore, terminology extraction is a very useful starting point for [[semantic similarity]], [[knowledge management]], [[translation|human translation]] and [[machine translation]], etc.
Typically, approaches to automatic term extraction make use of linguistic processors ([[part of speech tagging]], [[phrase chunking]]) to extract terminological candidates, i.e. syntactically plausible terminological [[noun phrase]]s, NPs (e.g. compounds "credit card", adjective-NPs "local tourist information office", and prepositional-NPs "board of directors" - in English, the first two constructs are the most frequent). Terminological entries are then filtered from the candidate list using statistical and [[machine learning]] methods. Once filtered, because of their low ambiguity and high specificity, these terms are particularly useful for conceptualizing a knowledge domain or for supporting the creation of a [[Ontology_%28computer_science%29#Domain_ontologies_and_upper_ontologies|domain ontology]]. Furthermore, terminology extraction is a very useful starting point for [[semantic similarity]], [[knowledge management]], [[translation|human translation]] and [[machine translation]], etc.


==See also==
==See also==
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* [http://www.linguoc.cat/index_en.html Lexterm], a free/open-source Lexical Extractor for Terminology and Translation (mono- and bilingual extraction).
* [http://www.linguoc.cat/index_en.html Lexterm], a free/open-source Lexical Extractor for Terminology and Translation (mono- and bilingual extraction).
* [http://sematext.com/products/key-phrase-extractor/index.html Sematext Key Phrase Extractor], a package for extraction of Collocations, Statistically Improbable Phrases (SIPs), etc. by [[Sematext]]
* [http://sematext.com/products/key-phrase-extractor/index.html Sematext Key Phrase Extractor], a package for extraction of Collocations, Statistically Improbable Phrases (SIPs), etc. by [[Sematext]]
* [http://fivefilters.org/term-extraction/ Five Filters Term Extraction], a free software term extraction service [[web application]]
* [http://fivefilters.org/term-extraction/ Five Filters Term Extraction], a free software term extraction service web application
* [http://www.alchemyapi.com/api/keyword/ AlchemyAPI], a web-based multi-lingual keyword / terminology extraction API [[web application]]
* [http://www.alchemyapi.com/api/keyword/ AlchemyAPI], a web-based multi-lingual keyword / terminology extraction API web application
* [http://developer.zemanta.com/ Zemanta API], a web-based keyword extraction and disambiguation API by [[Zemanta]]
* [http://developer.zemanta.com/ Zemanta API], a web-based keyword extraction and disambiguation API by [[Zemanta]]
* [https://www.terms-gekko.com Terms-Gekko], online terminology extraction tool for translators and linguists by [http://www.gekko-labs.com Gekko-Labs]
* [https://www.terms-gekko.com Terms-Gekko], online terminology extraction tool for translators and linguists by [http://www.gekko-labs.com Gekko-Labs]
* [http://developer.yahoo.com/search/content/V1/termExtraction.html Yahoo Term Extraction] API [[web application]]
* [http://developer.yahoo.com/search/content/V1/termExtraction.html Yahoo Term Extraction] API web application
* [http://www-01.ibm.com/software/globalization/topics/terminology/introduction.html Introduction to terminology management], by [[IBM]]
* [http://www-01.ibm.com/software/globalization/topics/terminology/introduction.html Introduction to terminology management], by [[IBM]]
* [http://www.nactem.ac.uk/software/termine/ TerMine], a term management system by the UK's [[National Centre for Text Mining]]. [[web application]]
* [http://www.nactem.ac.uk/software/termine/ TerMine], a term management system by the UK's [[National Centre for Text Mining]]. web application
* [http://lcl2.di.uniroma1.it/termextractor TermExtractor], a free terminology extraction [[web application]]
* [http://lcl2.di.uniroma1.it/termextractor TermExtractor], a free terminology extraction web application
* [http://labs.translated.net/terminology-extraction/ TermFinder], free online terminology extractor [[web application]]
* [http://labs.translated.net/terminology-extraction/ TermFinder], free online terminology extractor web application
* [http://www.termserver.eu/cms/content/view/14/28/ Statistical Bilingual Terminology Extractor], online terminology extractor [[web application]]
* [http://www.termserver.eu/cms/content/view/14/28/ Statistical Bilingual Terminology Extractor], online terminology extractor web application
* [http://ngram.sourceforge.net Ngram Statistics Package], open source package for identifying collocations
* [http://ngram.sourceforge.net Ngram Statistics Package], open source package for identifying collocations
* [http://www.heartsome.de/en/termextraction.php Heartsome Araya Bilingual Terminology Extractor for TMX files], by Heartsome Europe
* [http://www.heartsome.de/en/termextraction.php Heartsome Araya Bilingual Terminology Extractor for TMX files], by Heartsome Europe
* [http://www.gabormelli.com/RKB/Terminology_Extraction_Task Gabor Melli's info page on terminology extraction]
* [http://www.gabormelli.com/RKB/Terminology_Extraction_Task Gabor Melli's info page on terminology extraction]
* [http://ultimate-research-assistant.com/ Ultimate Research Assistant], A free online literacy tool with strong multi-lingual terminology extraction capabilities and visualizations including bar charts, mind maps, and taxonomies. Includes XML web services for [http://www.ultimate-research-assistant.com/oem/informationextractorservice.htm term extraction], [http://ultimate-research-assistant.com/oem/TextSummarizerService.htm text summarization], and [http://ultimate-research-assistant.com/oem/ClusteringEngineService.htm taxonomy generation / clustering].
* [http://ultimate-research-assistant.com/ Ultimate Research Assistant], A free online literacy tool with strong multi-lingual terminology extraction capabilities and visualizations including bar charts, mind maps, and taxonomies. Includes XML web services for [http://www.ultimate-research-assistant.com/oem/informationextractorservice.htm term extraction], [http://ultimate-research-assistant.com/oem/TextSummarizerService.htm text summarization], and [http://ultimate-research-assistant.com/oem/ClusteringEngineService.htm taxonomy generation / clustering].
* [https://semantria.com/technology/entity-extraction Semantria], a web-based multi-lingual keyword, entity, and theme extraction SaaS API [[web application]]
* [https://semantria.com/technology/entity-extraction Semantria], a web-based multi-lingual keyword, entity, and theme extraction SaaS API web application
⚫
* [https://entityclassifier.eu EntityClassifier.eu], an English/German/Dutch entity extraction web application and SaaS API built on top of [[Linked Hypernyms Dataset]]

⚫
* [https://entityclassifier.eu EntityClassifier.eu], an English/German/Dutch entity extraction [[web application]] and SaaS API built on top of [[Linked Hypernyms Dataset]]


[[Category:Natural language processing]]
[[Category:Natural language processing]]

Revision as of 21:46, 23 April 2014

Part of a series on
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Related topics

Terminology mining, term extraction, term recognition, or glossary extraction, is a subtask of information extraction. The goal of terminology extraction is to automatically extract relevant terms from a given corpus.

In the semantic web era, a growing number of communities and networked enterprises started to access and interoperate through the internet. Modeling these communities and their information needs is important for several web applications, like topic-driven web crawlers,[1] web services,[2] recommender systems,[3] etc. The development of terminology extraction is essential to the language industry.

One of the first steps to model the knowledge domain of a virtual community is to collect a vocabulary of domain-relevant terms, constituting the linguistic surface manifestation of domain concepts. Several methods to automatically extract technical terms from domain-specific document warehouses have been described in the literature.[4][5][6][7][8][9][10][11][12][13][14][15][16]

Typically, approaches to automatic term extraction make use of linguistic processors (part of speech tagging, phrase chunking) to extract terminological candidates, i.e. syntactically plausible terminological noun phrases, NPs (e.g. compounds "credit card", adjective-NPs "local tourist information office", and prepositional-NPs "board of directors" - in English, the first two constructs are the most frequent). Terminological entries are then filtered from the candidate list using statistical and machine learning methods. Once filtered, because of their low ambiguity and high specificity, these terms are particularly useful for conceptualizing a knowledge domain or for supporting the creation of a domain ontology. Furthermore, terminology extraction is a very useful starting point for semantic similarity, knowledge management, human translation and machine translation, etc.

See also

References

  1. ^ Menczer F., Pant G. and Srinivasan P. Topic-Driven Crawlers: machine learning issues.
  2. ^ Fan J. and Kambhampati S. A Snapshot of Public Web Services, in ACM SIGMOD Record archive Volume 34 , Issue 1 (March 2005).
  3. ^ Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings. A market-based approach to recommender systems, in ACM Transactions on Information Systems (TOIS), 23(3), 2005.
  4. ^ Bourigault D. and Jacquemin C. Term Extraction+Term Clustering: an integrated platform for computer-aided terminology, in Proc. of EACL, 1999.
  5. ^ Collier, N.; Nobata, C.; Tsujii, J. (2002). "Automatic acquisition and classification of terminology using a tagged corpus in the molecular biology domain". Terminology. 7 (2): 239–257. doi:10.1075/term.7.2.07col.
  6. ^ K. Frantzi, S. Ananiadou and H. Mima. (2000). Automatic recognition of multi-word terms: the C-value/NC-value method. In: C. Nikolau and C. Stephanidis (Eds.) International Journal on Digital Libraries, Vol. 3, No. 2., pp. 115-130.
  7. ^ K. Frantzi, S. Ananiadou and J. Tsujii. (1998) The C-value/NC-value Method of Automatic Recognition of Multi-word Terms, In: ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries, pp. 585-604. [isbn: 3-540-65101-2]
  8. ^ L. Kozakov, Y. Park, T. Fin, Y. Drissi, Y. Doganata, and T. Cofino. (2004). "Glossary extraction and utilization in the information search and delivery system for IBM Technical Support" (PDF). IBM System Journal. 43 (3).{{cite journal}}: CS1 maint: multiple names: authors list (link)
  9. ^ Navigli R. and Velardi, P. Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites. Computational Linguistics. 30 (2), MIT Press, 2004, pp. 151-179
  10. ^ Y. Park, R. J. Byrd, B. Boguraev. "Automatic glossary extraction: beyond terminology identification", International Conference On Computational Linguistics, Proceedings of the 19th international conference on Computational linguistics - Taipei, Taiwan, 2002.
  11. ^ Sclano, F. and Velardi, P.. TermExtractor: a Web Application to Learn the Shared Terminology of Emergent Web Communities. To appear in Proc. of the 3rd International Conference on Interoperability for Enterprise Software and Applications (I-ESA 2007). Funchal (Madeira Island), Portugal, March 28–30th, 2007.
  12. ^ P. Velardi, R. Navigli, P. D'Amadio. Mining the Web to Create Specialized Glossaries, IEEE Intelligent Systems, 23(5), IEEE Press, 2008, pp. 18-25.
  13. ^ Wermter J. and Hahn U. Finding New terminology in Very large Corpora, in Proc. of K-CAP'05, October 2–5, 2005, Banff, Alberta, Canada
  14. ^ Wong, W., Liu, W. & Bennamoun, M. (2007) Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast. [isbn: 978-1-920682-51-4]
  15. ^ Wong, W., Liu, W. & Bennamoun, M. (2007) Determining Termhood for Learning Domain Ontologies in a Probabilistic Framework. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast. [isbn: 978-1-920682-51-4]
  16. ^ Wong, W., Liu, W. & Bennamoun, M. (2008). "Determination of Unithood and Termhood for Term Recognition". In M. Song and Y. Wu (ed.). Handbook of Research on Text and Web Mining Technologies. IGI Global. doi:10.4018/978-1-59904-990-8. ISBN 978-1-59904-990-8.{{cite book}}: CS1 maint: multiple names: authors list (link)
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