DocumentCode
2287702
Title
A commercial real estate investment analysis from CBR approach
Author
Liu, Jia-Li ; Yan, Xiang-Bin
Author_Institution
Sch. of Manage., Harbin Inst. of Technol., Harbin, China
fYear
2009
fDate
14-16 Sept. 2009
Firstpage
1921
Lastpage
1927
Abstract
Commercial real estate investment analysis is very important for the commercial real estate industry, which is influenced by a series of complicated and various factors. Previous research emphasized on a certain part of the investment analysis, such as, commercial real estate´s market position, location, marketing strategy, risk control. Most of present works are to establish evaluation index system for investment analysis, which cannot give valuable suggestions before the investment project is proposed. In this paper, CBR method is adopted to support the investment analysis. Two feature attribute sets are set up to represent each commercial real estate investment case, and a case retrieval mechanism integrate with fuzzy-AHP is designed to search the similar case. In addition, the case-base has the ability of self-learning through case retaining and case updating. An example is provided to explain the feasibility and efficiency of the CBR system.
Keywords
case-based reasoning; fuzzy set theory; investment; learning (artificial intelligence); real estate data processing; CBR approach; analytic hierarchy process; case retaining; case retrieval mechanism; case updating; case-based reasoning method; commercial real estate investment analysis; evaluation index system; fuzzy-AHP; marketing strategy; risk control; self-learning; Business; Conference management; Electrical equipment industry; Engineering management; Environmental economics; Humans; Investments; Risk analysis; Technology management; Unemployment; case representation; case-based reasoning; commercial real estate; fuzzy-AHP;
fLanguage
English
Publisher
ieee
Conference_Titel
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location
Moscow
Print_ISBN
978-1-4244-3970-6
Electronic_ISBN
978-1-4244-3971-3
Type
conf
DOI
10.1109/ICMSE.2009.5317745
Filename
5317745
Link To Document