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https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4695Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | De Silva, S.N. | - |
| dc.date.accessioned | 2023-06-22T06:14:37Z | - |
| dc.date.available | 2023-06-22T06:14:37Z | - |
| dc.date.issued | 2023-06-22 | - |
| dc.identifier.uri | https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4695 | - |
| dc.description.abstract | Online reviewsplayanintegralroleintheprocessofdecisionmakingamongthe consumers ofaproductorservice.Inthetravelandtourismindustrytravellerreviews and ratingsmakeasignificantimpactonthechoicesmadebytravellers.Existing rating systemsaredesignedtocollectoverallratingandplain-textreview.Arating of aparticularaspectisagoodmetricfortheserviceprovidertoimprovetheservice and consumertofindtheperfectfitwithoutreadingthroughreviews.Thereforea systematic approachforpredictingarating,fordifferentaspectcategoriesinreviews havebeenidentifiedasaneed.Thisstudyaimstointroduceasystematicapproach to calculatetheaspectcategorybasedratingofcustomerreviewsintraveltourism domain. ThisstudyadaptsanovelapproachAspect-Category-Opinion-Sentiment (ACOS)QuadrupleExtraction,withtheaimtoextractallaspect-category-opinion- sentiment quadruplesinareviewsentencewhileconsideringimplicitaspectsand opinions andfinallycalculatetheaspectbasedratinginthetravelreviews.The experimentresultsdemonstratethatthismethodiseffectiveingeneratingtheaspect based ratingeventhoughasmallnumber(782)ofreviewsentenceshavebeenused. | en_US |
| dc.language.iso | en_US | en_US |
| dc.title | Aspect Based Sentiment Analysis on Travel Review Rating Prediction | en_US |
| dc.type | Thesis | en_US |
| Appears in Collections: | 2022 | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2019 BA 005.pdf | 619.82 kB | Adobe PDF | View/Open |
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