An Intelligent Multimodal Sentiment Analysis and Emotion Detection Framwork for Multimedia Reviews

dc.contributor.guideSannakki, Sanjeev
dc.coverage.spatial
dc.creator.researcherHuddar, Mahesh
dc.date.accessioned2023-02-18T09:58:54Z
dc.date.available2023-02-18T09:58:54Z
dc.date.awarded2021
dc.date.completed2021
dc.date.registered2017
dc.description.abstractii newlineABSTRACT newlineThe data revolution is one of the most important features of this century. In the last two newlinedecades, due to the availability of low-cost Internet facilities, advancements in Word- newlineWide-Web, and the growth in social media sites, multimodal data has grown at an newlineexponential rate. Multimodal data analysis can be used in many fields like improving the newlinequality of life of a customer, improving the business by monitoring the perception of newlineconsumers towards products or services or brands, human-computer interaction, TV news newlinesummarization, online interview, student feedback analysis, etc. The extraction of newlinecontextual knowledge from the utterances of a video, efficient multimodal fusion, feature newlinealignment between multiple modalities, handling conversational videos, and optimal newlinefeature selection are important issues in multimodal sentiment analysis and emotion newlinedetection.
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/462659
dc.languageEnglish
dc.publisher.institutionKLS Gogte Institute of Technology
dc.publisher.placeBelagavi
dc.publisher.universityVisvesvaraya Technological University, Belagavi
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordComputer Science
dc.subject.keywordEngineering and Technology
dc.subject.keywordImaging Science and Photographic Technology
dc.titleAn Intelligent Multimodal Sentiment Analysis and Emotion Detection Framwork for Multimedia Reviews
dc.title.alternative
dc.type.degreePh.D.

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