Items with full text/Total items : 67621/67621 (100%)
Visitors : 23028867
Online Users : 76
Please use this identifier to cite or link to this item:
|Title: ||住宅補貼申請戶特徵對審查合格影響之研究;Residential subsidies in feature of applicants for influence of review qualifiers by using SIP clustering method|
|Keywords: ||住宅補貼;資料探勘;群啟發;分群;群聚;residential subsidies;data mining;the group inspired;clustering;swarm|
|Issue Date: ||2014-10-15 14:25:25 (UTC+8)|
;The existing housing situation in Taiwan –The history, development and modern changes of Taiwan’s economy have had a strong impact on Taiwan’s housing situation effecting the idea of home ownership. Although prices of homes have risen steadily since 1987, home sales have also continued to increase. At the same time average family income has risen to levels beyond the scope of reasonable pricing; and therefore home ownership rates for lower-income households has dropped. This is also the reason why a ‘free market’ system cannot be enforced during these periods of rapid expansion, so the establishment of housing policies to support the disadvantaged is essential.
In accordance with the original structure, various policy measures were established based on occupation and the background of the applicant, with homogeneous interest rates and policy measures. These were dispersed and handled separately by several ministries, resulting in an efficient and effective use of resources and manpower; but not completely efficient. On 3 August 2006, the Council for Economic Affairs proposed that ‘Relative departments’ would conduct a professional review of the Residential Subsidy Program, since the program was based on subsidies that were approved before the year of 2005; and in the future would operate at the same level, and will be managed by the Ministry of the Interior.
Since the inception of the subsidy program, the number of applicants exceeds 10,000 annually. This is a sizeable database. In addition to using traditional, statistical methods to analyze the basics, and also because of the vast amount of data for analyzing the results of the data mining, this study is in the use of data-mining algorithms - inspired by the group to apply for housing subsidy. Data for ‘clustering’ by individual groups reveals the unique nature of each group, and provides follow-up for operational and policy changes to each related reference.
In its broadest scope, results can be realized regarding the economic situation of housing subsidies in a weak economy; but not necessarily aimed at ‘vulnerable’ groups. Within the program, assistance through a number of grants and benefits has existed for years without equality necessarily being directed to the economically disadvantaged groups. Finally, this research can provide data for the establishment of social benefits such as housing subsidies to the relevant authorities of the Ministry of the Interior to assist in the development of housing policy adjustments.
|Appears in Collections:||[土木工程研究所] 博碩士論文|
Files in This Item:
All items in NCUIR are protected by copyright, with all rights reserved.
::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期：8-24-2009 :::