完整後設資料紀錄
DC 欄位語言
dc.contributor.authorChen, Zhen-Huaen_US
dc.contributor.authorChou, Shing-Huaen_US
dc.contributor.authorTsai, Ching-Tsorngen_US
dc.contributor.authorChern, Johnen_US
dc.contributor.authorYuan, Shyan-Mingen_US
dc.date.accessioned2017-04-21T06:50:10Z-
dc.date.available2017-04-21T06:50:10Z-
dc.date.issued2015en_US
dc.identifier.isbn978-1-4673-8270-0en_US
dc.identifier.urihttp://hdl.handle.net/11536/135746-
dc.description.abstractCurrently, people obtained housing information from relatives, friends, sale representatives from model home, Realty networks, or government. It is difficult to get the housing-related information from these resources and hard to compare. Therefore, we proposed a public inquiry website called Housing Price Analysis using information from public websites to do statistical analyses based on the total ratio of "average value" and "standard deviation". People can use this website to get better understanding of price trend in certain area. This website will compare all records on public realty websites and government system based on same area with similar size of houses, number of rooms, age of house, etc. By using this system, users can get better understanding the trend of housing prices.en_US
dc.language.isoen_USen_US
dc.subjectBig Dataen_US
dc.subjectOpen Datalen_US
dc.subjectDataseten_US
dc.titleBig Data:Open Data and Realty Website Analysisen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2015 8TH INTERNATIONAL CONFERENCE ON UBI-MEDIA COMPUTING (UMEDIA) CONFERENCE PROCEEDINGSen_US
dc.citation.spage84en_US
dc.citation.epage88en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000380425200016en_US
dc.citation.woscount0en_US
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