UCD : Diachronic Text Classification with Character, Word, and Syntactic N-grams

DC FieldValueLanguage
dc.contributor.authorSzymanski, Terrence-
dc.contributor.authorLynch, Gerard-
dc.date.accessioned2015-08-26T12:03:01Z-
dc.date.available2015-08-26T12:03:01Z-
dc.date.issued2015-06-05-
dc.identifier.urihttp://hdl.handle.net/10197/6846-
dc.descriptionProceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015). United Statesen
dc.description.abstractWe present our submission to SemEval-2015Task 7: Diachronic Text Evaluation, in whichwe approach the task of assigning a date toa text as a multi-class classification problem.We extract n-gram features from the text atthe letter, word, and syntactic level, and usethese to train a classifier on date-labeled trainingdata. We also incorporate date probabilitiesof syntactic features as estimated from avery large external corpus of books. Our systemachieved the highest performance of allsystems on subtask 2: identifying texts by specifictime language use.en
dc.description.sponsorshipEnterprise Irelanden
dc.description.sponsorshipScience Foundation Irelanden
dc.language.isoenen
dc.subjectMachine Learning & Statisticsen
dc.subjectStylistic classificationen
dc.titleUCD : Diachronic Text Classification with Character, Word, and Syntactic N-gramsen
dc.typeConference Publicationen
dc.internal.webversionshttp://alt.qcri.org/semeval2015/-
dc.statusPeer revieweden
dc.neeo.contributorSzymanski|Terrence|aut|-
dc.neeo.contributorLynch|Gerard|aut|-
dc.date.updated2015-08-17T14:14:17Z-
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Computer Science Research Collection
Insight Research Collection
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