DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Zae Myung | ko |
dc.contributor.author | Jeong, Young-Seob | ko |
dc.contributor.author | Hyeon, Jonghwan | ko |
dc.contributor.author | Oh, Hyngrai | ko |
dc.contributor.author | Choi, Ho-Jin | ko |
dc.date.accessioned | 2016-12-01T06:58:20Z | - |
dc.date.available | 2016-12-01T06:58:20Z | - |
dc.date.created | 2016-06-10 | - |
dc.date.created | 2016-06-10 | - |
dc.date.issued | 2016-01 | - |
dc.identifier.citation | International Journal of Computing, Communication and Instrumentation Engineering, v.3, no.1, pp.96 - 101 | - |
dc.identifier.issn | 2349-1469 | - |
dc.identifier.uri | http://hdl.handle.net/10203/214545 | - |
dc.description.abstract | Intent classification refers to the process of identifying a set of intents of interest that appear in a given document. This work considers the task of annotating travel-related reviews with travel intents that best represent the reviewer's reason for visiting the place of interest (POI). A domain-tailored word embedding model is learned to construct intent-specific feature vectors, thereby improving classification accuracy. The feasibility of multiclass intent classification is explored using an intent corpus, consisting of 6,560 labelled reviews. | - |
dc.language | English | - |
dc.publisher | International Institute of Engineers | - |
dc.title | Classifying Travel-related Intents in Textual Data | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 3 | - |
dc.citation.issue | 1 | - |
dc.citation.beginningpage | 96 | - |
dc.citation.endingpage | 101 | - |
dc.citation.publicationname | International Journal of Computing, Communication and Instrumentation Engineering | - |
dc.identifier.doi | 10.15242/IJCCIE.ER01161004 | - |
dc.contributor.localauthor | Choi, Ho-Jin | - |
dc.contributor.nonIdAuthor | Oh, Hyngrai | - |
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