95:
590:. Noun phrases include compounds (e.g. "credit card"), adjective noun phrases (e.g. "local tourist information office"), and prepositional noun phrases (e.g. "board of directors"). In English, the first two (compounds and adjective noun phrases) are the most frequent. Terminological entries are then filtered from the candidate list using statistical and
25:
934:: 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.
630:
statistics, candidates for term translations can be obtained. Bilingual terminology can be extracted also from comparable corpora (corpora containing texts within the same text type, domain but not translations of documents between each other).
594:
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
1121:
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43:
455:
1870:
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358:
914:, International Conference On Computational Linguistics, Proceedings of the 19th international conference on Computational linguistics - Taipei, Taiwan, 2002.
791:
Collier, N.; Nobata, C.; Tsujii, J. (2002). "Automatic acquisition and classification of terminology using a tagged corpus in the molecular biology domain".
467:
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978:
944:
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911:
758:
575:. Several methods to automatically extract technical terms from domain-specific document warehouses have been described in the literature.
1834:
1441:
353:
834:, In: ECDL '98 Proceedings of the Second European Conference on Research and Advanced Technology for Digital Libraries, pp. 585-604.
445:
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343:
61:
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1010:
Alrehamy, Hassan H; Walker, Coral (2018). "SemCluster: Unsupervised
Automatic Keyphrase Extraction Using Affinity Propagation".
699:
Alrehamy, Hassan H; Walker, Coral (2018). "SemCluster: Unsupervised
Automatic Keyphrase Extraction Using Affinity Propagation".
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In: C. Nikolau and C. Stephanidis (Eds.) International
Journal on Digital Libraries, Vol. 3, No. 2., pp. 115-130.
640:
571:
is to collect a vocabulary of domain-relevant terms, constituting the linguistic surface manifestation of domain
479:
119:
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1500:
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era, a growing number of communities and networked enterprises started to access and interoperate through the
853:"Glossary extraction and utilization in the information search and delivery system for IBM Technical Support"
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901:. Proceedings of Recent Advances in Natural Language Processing (RANLP 2015), 2015, pp. 473–479
598:
or a terminology base. Furthermore, terminology extraction is a very useful starting point for
1813:
1525:
1333:
1244:
1023:
994:
974:
835:
712:
561:
374:
225:
109:
529:. The goal of terminology extraction is to automatically extract relevant terms from a given
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1575:
1550:
1351:
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1045:"TExSIS: Bilingual terminology extraction from parallel corpora using chunk-based alignment"
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971:
Determining
Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency
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745:
732:
1510:
1490:
1214:
772:
Term
Extraction+Term Clustering: an integrated platform for computer-aided terminology
578:
Typically, approaches to automatic term extraction make use of linguistic processors (
1864:
1773:
1585:
1565:
1346:
627:
297:
200:
586:) to extract terminological candidates, i.e. syntactically plausible terminological
1753:
537:
1014:. Advances in Intelligent Systems and Computing. Vol. 650. pp. 222–235.
927:
703:. Advances in Intelligent Systems and Computing. Vol. 650. pp. 222–235.
544:. Modeling these communities and their information needs is important for several
1019:
708:
1710:
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991:
Determining
Termhood for Learning Domain Ontologies in a Probabilistic Framework
957:
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TBXTools: A Free, Fast and
Flexible Tool for Automatic Terminology Extraction
851:
L. Kozakov; Y. Park; T. Fin; Y. Drissi; Y. Doganata & T. Cofino. (2004).
1181:
1060:
266:
1084:
Sharoff, Serge; Rapp, Reinhard; Zweigenbaum, Pierre; Fung, Pascale (2013),
1069:
886:
Learning Domain
Ontologies from Document Warehouses and Dedicated Web Sites
831:
804:
560:, etc. The development of terminology extraction is also essential to the
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1600:
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871:
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The C-value/NC-value Method of
Automatic Recognition of Multi-word Terms
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1631:
1505:
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1164:
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819:
Automatic recognition of multi-word terms: the C-value/NC-value method.
261:
993:. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast.
973:. In: 6th Australasian Conference on Data Mining (AusDM); Gold Coast.
1159:
1154:
420:
415:
748:, in ACM SIGMOD Record archive Volume 34 , Issue 1 (March 2005).
1849:
1485:
912:"Automatic glossary extraction: beyond terminology identification"
960:, in Proc. of K-CAP'05, October 2–5, 2005, Banff, Alberta, Canada
888:. Computational Linguistics. 30 (2), MIT Press, 2004, pp. 151-179
761:, in ACM Transactions on Information Systems (TOIS), 23(3), 2005.
1371:
1103:
947:, IEEE Intelligent Systems, 23(5), IEEE Press, 2008, pp. 18-25.
1646:
18:
622:
The methods for terminology extraction can be applied to
39:
1043:
Macken, Lieve; Lefever, Els; Hoste, Veronique (2013).
1827:
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34:
may be too technical for most readers to understand
757:Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings.
945:Mining the Web to Create Specialized Glossaries
830:K. Frantzi, S. Ananiadou and J. Tsujii. (1998)
1012:Advances in Computational Intelligence Systems
817:K. Frantzi, S. Ananiadou and H. Mima. (2000).
759:A market-based approach to recommender systems
733:Topic-Driven Crawlers: machine learning issues
701:Advances in Computational Intelligence Systems
1115:
989:Wong, W., Liu, W. & Bennamoun, M. (2007)
969:Wong, W., Liu, W. & Bennamoun, M. (2007)
958:Finding New terminology in Very large Corpora
487:
8:
1533:
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494:
480:
73:
1068:
62:Learn how and when to remove this message
46:, without removing the technical details.
691:
366:
335:
289:
233:
187:
101:
85:
731:Menczer F., Pant G. and Srinivasan P.
446:Bhagavad-gita translations by language
1087:Building and Using Comparable Corpora
943:P. Velardi, R. Navigli, P. D'Amadio.
303:Internationalization and localization
44:make it understandable to non-experts
7:
1871:Tasks of natural language processing
1581:Simple Knowledge Organization System
910:Y. Park, R. J. Byrd, B. Boguraev.
567:One of the first steps to model a
436:Books and magazines on translation
14:
1596:Thesaurus (information retrieval)
746:A Snapshot of Public Web Services
16:Subtask of information extraction
618:Bilingual terminology extraction
93:
23:
770:Bourigault D. and Jacquemin C.
1177:Natural language understanding
468:Kural translations by language
441:Bible translations by language
216:Dynamic and formal equivalence
1:
1701:Optical character recognition
456:List of most translated works
257:Translation management system
1394:Multi-document summarization
1020:10.1007/978-3-319-66939-7_19
709:10.1007/978-3-319-66939-7_19
1876:Library science terminology
1724:Latent Dirichlet allocation
1696:Natural language generation
1561:Machine-readable dictionary
1556:Linguistic Linked Open Data
1131:Natural language processing
897:Oliver, A. and Vàzquez, M.
884:Navigli R. and Velardi, P.
651:Natural language processing
1897:
1476:Explicit semantic analysis
1225:Deep linguistic processing
744:Fan J. and Kambhampati S.
1319:Word-sense disambiguation
1172:Computational linguistics
1093:, Berlin: Springer-Verlag
781:, in Proc. of EACL, 1999.
641:Computational linguistics
1845:Natural Language Toolkit
1769:Pronunciation assessment
1671:Automatic identification
1501:Latent semantic analysis
1457:Distributional semantics
1342:Compound-term processing
1240:Named-entity recognition
431:Journalistic translation
1749:Automated essay scoring
1719:Document classification
1386:Automatic summarization
1061:10.1075/term.19.1.01mac
956:Wermter J. and Hahn U.
313:Video game localization
221:Contrastive linguistics
1606:Universal Dependencies
1299:Terminology extraction
1282:Semantic decomposition
1277:Semantic role labeling
1267:Part-of-speech tagging
1235:Information extraction
1220:Coreference resolution
1210:Collocation extraction
805:10.1075/term.7.2.07col
580:part of speech tagging
527:information extraction
507:Terminology extraction
396:Telephone interpreting
282:Multimedia translation
1881:Computing terminology
1367:Sentence segmentation
626:. Combined with e.g.
328:Software localization
308:Language localization
211:Translation criticism
140:Linguistic validation
1819:Voice user interface
1530:datasets and corpora
1471:Document-term matrix
1324:Word-sense induction
604:knowledge management
548:, like topic-driven
323:Website localization
1799:Interactive fiction
1729:Pachinko allocation
1686:Speech segmentation
1642:Google Ngram Viewer
1414:Machine translation
1404:Text simplification
1399:Sentence extraction
1287:Semantic similarity
872:10.1147/sj.433.0546
860:IBM Systems Journal
681:Text simplification
612:machine translation
600:semantic similarity
558:recommender systems
390:Video relay service
247:Machine translation
206:Translation project
196:Translation studies
1809:Question answering
1681:Speech recognition
1546:Corpus linguistics
1526:Language resources
1309:Textual entailment
1292:Sentiment analysis
777:2006-06-19 at the
666:Taxonomy (general)
525:) is a subtask of
252:Mobile translation
1858:
1857:
1814:Virtual assistant
1739:Computer-assisted
1665:
1664:
1422:Computer-assisted
1380:
1379:
1372:Word segmentation
1334:Text segmentation
1272:Semantic analysis
1260:Syntactic parsing
1245:Ontology learning
1029:978-3-319-66938-0
999:978-1-920682-51-4
979:978-1-920682-51-4
718:978-3-319-66938-0
608:human translation
562:language industry
521:, or terminology
517:extraction, term
504:
503:
375:Untranslatability
226:Polysystem theory
72:
71:
64:
1888:
1835:Formal semantics
1784:Natural language
1691:Speech synthesis
1673:and data capture
1576:Semantic network
1551:Lexical resource
1534:
1352:Lexical analysis
1330:
1255:Semantic parsing
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661:Subject indexing
624:parallel corpora
592:machine learning
569:knowledge domain
546:web applications
496:
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451:Translated books
401:Language barrier
318:Dub localization
97:
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1803:Syntax guessing
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1764:Predictive text
1759:Grammar checker
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1627:Bank of English
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1230:Distant reading
1205:Argument mining
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1187:Text processing
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1070:1854/LU-2128573
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656:Domain ontology
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596:domain ontology
584:phrase chunking
509:(also known as
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406:Fan translation
385:Transliteration
175:Sense-for-sense
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40:help improve it
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380:Transcription
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344:Associations
290:Localization
234:Technologies
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1711:Topic model
1591:Text corpus
1437:Statistical
1304:Text mining
1145:AI-complete
1055:(1): 1–30.
1049:Terminology
928:Velardi, P.
793:Terminology
676:Text mining
671:Terminology
519:recognition
463:Translators
277:Postediting
272:Pre-editing
87:Translation
1865:Categories
1432:Rule-based
1314:Truecasing
1182:Stop words
924:Sclano, F.
687:References
426:Scanlation
267:Subtitling
180:Homophonic
150:Regulatory
1741:reviewing
1539:standards
1537:Types and
155:Technical
1657:Wikidata
1637:FrameNet
1622:BabelNet
1601:Treebank
1571:PropBank
1516:Word2vec
1481:fastText
1362:Stemming
775:Archived
646:Glossary
635:See also
573:concepts
542:internet
515:glossary
165:Cultural
115:Literary
79:a series
77:Part of
1828:Related
1794:Chatbot
1652:WordNet
1632:DBpedia
1506:Seq2seq
1250:Parsing
1165:Trigram
614:, etc.
536:In the
359:Schools
262:Dubbing
145:Medical
38:Please
1801:(c.f.
1459:models
1447:Neural
1160:Bigram
1155:n-gram
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523:mining
421:Fandub
416:Fansub
349:Awards
188:Theory
1850:spaCy
1495:large
1486:GloVe
1091:(PDF)
856:(PDF)
392:(VRS)
135:Kural
130:Quran
125:Bible
110:Legal
102:Types
1615:Data
1466:BERT
1024:ISBN
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926:and
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713:ISBN
610:and
511:term
1647:UBY
1065:hdl
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