How to Meet the Diverse Needs of Consumers: Big Data Mining based on Online Review

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dc.contributor.authorGu, Wei
dc.contributor.authorHu, Rui
dc.contributor.authorSong, Yanan
dc.date.accessioned2020-01-04T07:44:46Z
dc.date.available2020-01-04T07:44:46Z
dc.date.issued2020-01-07
dc.description.abstractThis article applied Word2vec and image mining on OCRs analysis. Data from Dianping.com showed that in Beijing, good taste is the primary factor for customers to choose a restaurant. Unlike the general opinion, careers and locations have little influence on cuisine choice in Beijing. Hot pot is the most popular one all over the city. Warm color, medium dark light and saturation with certain amount of grey are three key aspects for an enjoyable dining environment. Offline mouth to mouth recommendation is the most useful way to spread a restaurants reputation. So making the antecedent consumer satisfy is the most applied way to appeal new ones. This findings can help restaurant owners to run a better business and promote the satisfactory.
dc.format.extent10 pages
dc.identifier.doihttps://doi.org/10.24251/HICSS.2020.349
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64091
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSocial Media Management in Big Data Era
dc.subjectbig data
dc.subjectsocial media ocrs
dc.subjectconsumer preference
dc.subjectdining industry
dc.titleHow to Meet the Diverse Needs of Consumers: Big Data Mining based on Online Review
dc.typeConference Paper
dc.type.dcmiText

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