Please use this identifier to cite or link to this item: http://hdl.handle.net/10263/7301
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dc.contributor.authorPatel, Ashwani-
dc.date.accessioned2022-03-23T10:22:23Z-
dc.date.available2022-03-23T10:22:23Z-
dc.date.issued2021-07-
dc.identifier.citation25p.en_US
dc.identifier.urihttp://hdl.handle.net/10263/7301-
dc.descriptionUnder the guidance of Dr. Debapriyo Majumdaren_US
dc.description.abstractThe worldwide theatrical market had a box office of US $42.2 billion in 2019. In recent years it has been seen that it is growing even more and more, as a consequence urge to predict the success of the movie has increased. To inspect this issue various methodology has been proposed some of which rely on reviews and the trailer when most or all the budget of the movie has been enervated. To overcome this some recent papers have also used the plot summary of the movie to classify the movie as successful or not successful. In this work, we will try to predict the quality of the movie not only by using the plot summary but other metadata of the movie too. We have used the CMU corpus for the movie metadata and the IMDB database for the ratings. We have experimented with LSTM, ELMO, Sentiment analysis, and Transformer based architecture like BERT. We have experimented with all these and combined them to come up with a feature engineering architecture suitable for our task.en_US
dc.language.isoenen_US
dc.publisherIndian Statistical Institute, Kolkata.en_US
dc.relation.ispartofseriesDissertation;CS1916-
dc.subjectMovieen_US
dc.subjectMetadataen_US
dc.subjectPlot Summaryen_US
dc.titlePredicting Quality of Movie from Metadata and Plot Summaryen_US
dc.typeOtheren_US
Appears in Collections:Dissertations - M Tech (CS)

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