Prikaz osnovnih podataka o dokumentu
Estimating Market Value of Apartments Using the k-Nearest Neighbors Algorithm
Procena tržišne vrednosti stana metodom k-najbližih suseda
dc.creator | Dragojević, Marko | |
dc.creator | Stančić, Nikola | |
dc.date.accessioned | 2020-04-25T18:07:49Z | |
dc.date.available | 2020-04-25T18:07:49Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-86-80297-73-6 | |
dc.identifier.uri | https://grafar.grf.bg.ac.rs/handle/123456789/1920 | |
dc.description.abstract | The market value of apartments is, as the name itself suggests, defined by the sellers and the buyers through supply and demand – elements that collectively make up the market. Observing a large number of factors affecting the price of real estate is not an easy job. Price formation depends on both the characteristics of the apartment and the buyer’s value-system. The basic question that a rational customer asks himself is "why would I pay a larger sum of money for the same or practically same thing than what someone else paid for it just recently?". This fact leads to the conclusion that it is necessary to know the characteristics and prices of the real estates traded in the near past and in the close surrounding. A comparative way of customer’s thinking is the basic principle for defining one such model. This is a necessary but not sufficient condition. Models based on the machine learning algorithms (among them k-Nearest Neighbors algorithm) require having a larger amount of data, so that the made conclusions can be reliable, accurate, and precise. | en |
dc.description.abstract | Tržišnu vrednost stanova, kao što sama reč govori, definišu prodavci i kupci kroz ponudu i tražnju, koje u osnovi i čine samo tržište. Sagledavanje velikog broja faktora uticaja na cenu nepokretnosti nije nimalo lak posao. Formiranje cena zavisi kako od karakteristika stana, tako i od sistema vrednosti kupaca. „Zašto bih ja za istu ili sličnu stvar platio veći iznos nego što je neko drugi platio u neposrednoj prošlosti“ jeste osnovno pitanje koje racionalan kupac postavlja sebi. Ova činjenica dovodi do zaključka da je potrebno znati karakteristike i cene nepokretnosti koje su oglašene ili prometovane u neposrednoj prošlosti u bliskom okruženju. Komparativni način razmišljanja kupca je osnovni uslov i princip za definisanje jednog ovakvog modela. Ovo je neophodan, ali ne i dovoljan uslov. Modeli bazirani na algoritmima mašinskog učenja, kao što je i k-najbližih suseda, podrazumevaju poznavanje nešto veće količine kvalitetnih podataka, kako bi doneti zaključci bili pouzdani, tačni i precizni. | sr |
dc.language.iso | en | sr |
dc.publisher | Subotica : Građevinski fakultet Subotica | sr |
dc.relation | info:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/36020/RS// | sr |
dc.relation | info:eu-repo/grantAgreement/MESTD/Integrated and Interdisciplinary Research (IIR or III)/47014/RS// | sr |
dc.rights | openAccess | sr |
dc.source | 7th International Conference 'Contemporary Achievements in Civil Engineering 2019' | sr |
dc.subject | estimating market value | sr |
dc.subject | market of apartments | sr |
dc.subject | data mining | sr |
dc.subject | k-Nearest Neighbors algorithm | sr |
dc.subject | procena tržišne vrednosti | sr |
dc.subject | tržište stanova | sr |
dc.subject | zaključivanje iz podataka | sr |
dc.subject | metoda k-najbližih suseda | sr |
dc.title | Estimating Market Value of Apartments Using the k-Nearest Neighbors Algorithm | en |
dc.title | Procena tržišne vrednosti stana metodom k-najbližih suseda | sr |
dc.type | conferenceObject | sr |
dc.rights.license | ARR | sr |
dc.rights.holder | Građevinski fakultet Subotica | sr |
dc.citation.epage | 1069 | |
dc.citation.spage | 1059 | |
dc.citation.volume | 7 | |
dc.identifier.doi | 10.14415/konferencijaGFS2019.098 | |
dc.identifier.fulltext | https://grafar.grf.bg.ac.rs/bitstream/id/7371/bitstream_7371.pdf | |
dc.type.version | publishedVersion | sr |