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Similarity-Driven Visual-Interactive Prediction of Movie Ratings and Box Office Results

Similarity-Driven Visual-Interactive Prediction of Movie Ratings and Box Office Results

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AL-MASOUDI, Feeras, Daniel SEEBACHER, Mario SCHREINER, Manuel STEIN, Christian ROHRDANTZ, Fabian FISCHER, Svenja SIMON, Tobias SCHRECK, Daniel KEIM, 2013. Similarity-Driven Visual-Interactive Prediction of Movie Ratings and Box Office Results. IEEE VIS. Atlanta, Georgia, USA, 13. Okt 2013 - 18. Okt 2013. In: VIS 2013 : IEEE International Conference on Visual Analytics Science and Technology ; 13 - 18 October 2013, Atlanta, Georgia, USA. IEEE VIS. Atlanta, Georgia, USA, 13. Okt 2013 - 18. Okt 2013

@inproceedings{Al-Masoudi2013Simil-26532, title={Similarity-Driven Visual-Interactive Prediction of Movie Ratings and Box Office Results}, year={2013}, booktitle={VIS 2013 : IEEE International Conference on Visual Analytics Science and Technology ; 13 - 18 October 2013, Atlanta, Georgia, USA}, author={Al-Masoudi, Feeras and Seebacher, Daniel and Schreiner, Mario and Stein, Manuel and Rohrdantz, Christian and Fischer, Fabian and Simon, Svenja and Schreck, Tobias and Keim, Daniel} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/26532"> <dcterms:abstract xml:lang="eng">We present an approach developed in course of the VAST 2013 Mini Challenge: Visualize the Box Office. We follow a similaritydriven methodology to predict ratings and box office results based on historic data. An array of interactive visualizations allow analysts to explore structured and unstructured data, activate their domain background knowledge, and come up with predictions as a weighted sum of historically observed figures. We describe the workflow, our developed system, present results obtained during the Challenge execution, and discuss our method in light of extension possibilities.</dcterms:abstract> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-26T10:26:10Z</dcterms:available> <dcterms:rights rdf:resource="http://nbn-resolving.org/urn:nbn:de:bsz:352-20140905103605204-4002607-1"/> <dc:contributor>Stein, Manuel</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-26T10:26:10Z</dc:date> <dc:creator>Seebacher, Daniel</dc:creator> <dc:contributor>Fischer, Fabian</dc:contributor> <dcterms:issued>2013</dcterms:issued> <dc:language>eng</dc:language> <dc:creator>Fischer, Fabian</dc:creator> <dc:creator>Al-Masoudi, Feeras</dc:creator> <dc:contributor>Rohrdantz, Christian</dc:contributor> <dc:creator>Stein, Manuel</dc:creator> <dc:rights>deposit-license</dc:rights> <dc:contributor>Seebacher, Daniel</dc:contributor> <dc:creator>Keim, Daniel</dc:creator> <dcterms:title>Similarity-Driven Visual-Interactive Prediction of Movie Ratings and Box Office Results</dcterms:title> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/26532"/> <dc:creator>Simon, Svenja</dc:creator> <dc:contributor>Simon, Svenja</dc:contributor> <dc:creator>Schreck, Tobias</dc:creator> <dc:creator>Schreiner, Mario</dc:creator> <dc:contributor>Schreiner, Mario</dc:contributor> <dc:creator>Rohrdantz, Christian</dc:creator> <dc:contributor>Schreck, Tobias</dc:contributor> <dc:contributor>Al-Masoudi, Feeras</dc:contributor> <dcterms:bibliographicCitation>Vortrag gehalten bei: VIS 2013 : IEEE International Conference on Visual Analytics Science and Technology ; 13-18 October 2013, Atlanta, Georgia, USA</dcterms:bibliographicCitation> <dc:contributor>Keim, Daniel</dc:contributor> </rdf:Description> </rdf:RDF>

Dateiabrufe seit 01.10.2014 (Informationen über die Zugriffsstatistik)

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