| dc.contributor | 會計系 | zh_Tw |
| dc.creator (作者) | Yang, Hsiao-Fang;Seng, Jia-Lang | en_US |
| dc.creator (作者) | 諶家蘭 | zh_TW |
| dc.date (日期) | 2017-04 | en_US |
| dc.date.accessioned | 3-Aug-2017 14:27:58 (UTC+8) | - |
| dc.date.available | 3-Aug-2017 14:27:58 (UTC+8) | - |
| dc.date.issued (上傳時間) | 3-Aug-2017 14:27:58 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/111640 | - |
| dc.description.abstract (摘要) | In recent years, semi-structured and unstructured data have received substantial attention. Previous studies on sentiment analysis and opinion mining have indicated that media information features sentiment factors that can affect investor decisions. However, few studies have explored the correlation between news sentiment and housing prices; hence, the present study was conducted to investigate this correlation. A method was proposed to collect and filter news information and analyze the correlation between news sentiment and housing prices. The results indicate that news sentiment can serve as a reference for evaluating housing price trends. © Springer International Publishing AG 2017. | en_US |
| dc.format.extent | 212 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10192 LNAI, 170-179 | en_US |
| dc.relation (關聯) | 9th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2017; Kanazawa; Japan; 3 April 2017 到 5 April 2017; 代碼 190369 | en_US |
| dc.subject (關鍵詞) | Costs; Data mining; Database systems; Filtration; Housing prices; Information feature; News information; Opinion mining; Scoring models; Semi-structured; Sentiment analysis; Unstructured data; Housing | en_US |
| dc.title (題名) | Using sentiment analysis to explore the association between news and housing prices | en_US |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1007/978-3-319-54430-4_17 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1007/978-3-319-54430-4_17 | |
