Aspect Level Sentiment Polarity Classification Using Sequence Attention Mechanism with Amplified Intelligence

dc.contributor.guideVadivu G
dc.coverage.spatial
dc.creator.researcherSindhu C
dc.date.accessioned2021-09-20T04:24:42Z
dc.date.available2021-09-20T04:24:42Z
dc.date.awarded
dc.date.completed2021
dc.date.registered
dc.description.abstractWith the exploding web technology, user generated content is all over the web and is accessible almost everywhere in this world. Such an accessibility has paved way for an easier suggestion seeking paradigm. In this fast-paced world, we humans find no time to stand and stare, which well suits this scenario, where, we don t want to read through each and every review of a product or a service. Sentiment Analysis is, thus an inevitable process, which helps every manufacturer and brand-owner to analyse the pros and cons of his own item and his competing products. Furthermore, be it any service or product, the experience shared about it is multi-dimensional with loads of emotions splashed into it newline
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/341153
dc.languageEnglish
dc.publisher.institutionDepartment of Computer Science Engineering
dc.publisher.placeKattankulathur
dc.publisher.universitySRM University
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordAutomation and Control Systems
dc.subject.keywordComputer Science
dc.subject.keywordEngineering and Technology
dc.titleAspect Level Sentiment Polarity Classification Using Sequence Attention Mechanism with Amplified Intelligence
dc.title.alternative
dc.type.degreePh.D.

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