{"_id":"YLp8YuRbNHMJvYzRc","bibbaseid":"abramowicz-wisniewski-proximitywindowcontextmethodfortermextractioninontologylearningfromtext-2008","authorIDs":[],"author_short":["Abramowicz, W.","Wisniewski, M."],"bibdata":{"title":"Proximity Window Context Method for Term Extraction in Ontology Learning from Text","type":"article","year":"2008","identifiers":"[object Object]","pages":"215-219","websites":"http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4624718","publisher":"Ieee","editors":"[object Object],[object Object]","id":"4af31846-0aab-34cd-aa09-6f829fc7b341","created":"2011-12-29T19:53:53.000Z","file_attached":false,"profile_id":"5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6","group_id":"066b42c8-f712-3fc3-abb2-225c158d2704","last_modified":"2017-03-14T14:36:19.698Z","tags":"term extraction","read":false,"starred":"true","authored":false,"confirmed":"true","hidden":false,"citation_key":"Abramowicz2008","private_publication":false,"abstract":"The ontology learning from text cycle consists of the consecutive phases of term, synonym, concept, taxonomy and relation extraction. The paper touches the problems of a low efficiency in the current term extraction methods which are handled by a combination of statistic (frequency-based) and linguistic approaches.We present a novel method to extract terms that uses only shallow linguistic information. It is proposed to explore a different set of linguistic layers and support a classic POS n-gram model with additional context information based on proximity window features. The method is evaluated on two substantially different corpora to produce better results than the classic measures, including standard n-gram models and frequency-based approaches.","bibtype":"article","author":"Abramowicz, Witold and Wisniewski, Marek","journal":"2008 19th International Conference on Database and Expert Systems Applications","bibtex":"@article{\n title = {Proximity Window Context Method for Term Extraction in Ontology Learning from Text},\n type = {article},\n year = {2008},\n identifiers = {[object Object]},\n pages = {215-219},\n websites = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4624718},\n publisher = {Ieee},\n editors = {[object Object],[object Object]},\n id = {4af31846-0aab-34cd-aa09-6f829fc7b341},\n created = {2011-12-29T19:53:53.000Z},\n file_attached = {false},\n profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},\n group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},\n last_modified = {2017-03-14T14:36:19.698Z},\n tags = {term extraction},\n read = {false},\n starred = {true},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Abramowicz2008},\n private_publication = {false},\n abstract = {The ontology learning from text cycle consists of the consecutive phases of term, synonym, concept, taxonomy and relation extraction. The paper touches the problems of a low efficiency in the current term extraction methods which are handled by a combination of statistic (frequency-based) and linguistic approaches.We present a novel method to extract terms that uses only shallow linguistic information. It is proposed to explore a different set of linguistic layers and support a classic POS n-gram model with additional context information based on proximity window features. The method is evaluated on two substantially different corpora to produce better results than the classic measures, including standard n-gram models and frequency-based approaches.},\n bibtype = {article},\n author = {Abramowicz, Witold and Wisniewski, Marek},\n journal = {2008 19th International Conference on Database and Expert Systems Applications}\n}","author_short":["Abramowicz, W.","Wisniewski, M."],"urls":{"Website":"http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4624718"},"bibbaseid":"abramowicz-wisniewski-proximitywindowcontextmethodfortermextractioninontologylearningfromtext-2008","role":"author","downloads":0,"html":""},"bibtype":"article","creationDate":"2020-02-06T23:48:11.878Z","downloads":0,"keywords":[],"search_terms":["proximity","window","context","method","term","extraction","ontology","learning","text","abramowicz","wisniewski"],"title":"Proximity Window Context Method for Term Extraction in Ontology Learning from Text","year":2008}