Mladen Vidović, Ivan Radosavljević, Aleksandra Mitrovic, Z. Konjovic, Dobrivoje Đurić, V. Matic, M. Simić, Miljan Vucetic, Gardelito HewAKee, Miloš Stanković, Kristina Kaličanin, Milica Čolović, A. Njeguš, V. Mitić, Aleksa Ćuk, Branivoj Miljković, Miloš Todorović, Aleksandar Ivanović, M. Zivkovic, E. Mele, Marlene Gröblacher, Vule Mizdraković, Danica Rajin, Marijana Petrović, Tijana Radojević, Ričardas Butėnas, Zlata Bracanović, Nemanja Bošnjak, Milica Peric, M. Stanišić, Nikica Radović, J. Nikolic, B. Vakanjac, L. Amidžić, Tanita Đumić, Vladimir Mirković, Jelena Lukic, Vesna Martin, I. Miljković, M. Dobrojevic, J. Pršić, Vesna Ristić Vakanjac, M. Trkulja, M. Ilić, S. D. Milošević, Nikola Dražić, J. Milovanovic, G. Dražić, E. Marišová, Maja Gligorić, Marija Kostić, J. Gržinić, E. Pap, M. Petković, Ana Blagojević, S. Stanišić, Jelena Teodorović, Slađana Čabrilo
{"title":"基于网络广告的房地产价格预测训练数据构建","authors":"Mladen Vidović, Ivan Radosavljević, Aleksandra Mitrovic, Z. Konjovic, Dobrivoje Đurić, V. Matic, M. Simić, Miljan Vucetic, Gardelito HewAKee, Miloš Stanković, Kristina Kaličanin, Milica Čolović, A. Njeguš, V. Mitić, Aleksa Ćuk, Branivoj Miljković, Miloš Todorović, Aleksandar Ivanović, M. Zivkovic, E. Mele, Marlene Gröblacher, Vule Mizdraković, Danica Rajin, Marijana Petrović, Tijana Radojević, Ričardas Butėnas, Zlata Bracanović, Nemanja Bošnjak, Milica Peric, M. Stanišić, Nikica Radović, J. Nikolic, B. Vakanjac, L. Amidžić, Tanita Đumić, Vladimir Mirković, Jelena Lukic, Vesna Martin, I. Miljković, M. Dobrojevic, J. Pršić, Vesna Ristić Vakanjac, M. Trkulja, M. Ilić, S. D. Milošević, Nikola Dražić, J. Milovanovic, G. Dražić, E. Marišová, Maja Gligorić, Marija Kostić, J. Gržinić, E. Pap, M. Petković, Ana Blagojević, S. Stanišić, Jelena Teodorović, Slađana Čabrilo","doi":"10.15308/SINTEZA-2019-388-393","DOIUrl":null,"url":null,"abstract":"The paper presents a model for constructing a data set aimed at predicting a price of a real estate (houses and flats) from the standard Internet ads. The model for predicting a real estate price includes, in addition to standard real estate's features (area, number of bedrooms, etc.) appearing in ad, attractiveness of a real estate location as well as information on some additional interior facilities (e.g., refrigerator, dish-washing machine, stove, etc.). The proposed training set construction model uses OpenStreetMap's Overpass API for determining attractiveness of a real estate's location, and a convolution neural network for detecting interior facilities from real estate photos.","PeriodicalId":342313,"journal":{"name":"Proceedings of the International Scientific Conference - Sinteza 2019","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Construction of Training Data for Price Prediction of a Real Estate from Internet Ads\",\"authors\":\"Mladen Vidović, Ivan Radosavljević, Aleksandra Mitrovic, Z. Konjovic, Dobrivoje Đurić, V. Matic, M. Simić, Miljan Vucetic, Gardelito HewAKee, Miloš Stanković, Kristina Kaličanin, Milica Čolović, A. Njeguš, V. Mitić, Aleksa Ćuk, Branivoj Miljković, Miloš Todorović, Aleksandar Ivanović, M. Zivkovic, E. Mele, Marlene Gröblacher, Vule Mizdraković, Danica Rajin, Marijana Petrović, Tijana Radojević, Ričardas Butėnas, Zlata Bracanović, Nemanja Bošnjak, Milica Peric, M. Stanišić, Nikica Radović, J. Nikolic, B. Vakanjac, L. Amidžić, Tanita Đumić, Vladimir Mirković, Jelena Lukic, Vesna Martin, I. Miljković, M. Dobrojevic, J. Pršić, Vesna Ristić Vakanjac, M. Trkulja, M. Ilić, S. D. Milošević, Nikola Dražić, J. Milovanovic, G. Dražić, E. Marišová, Maja Gligorić, Marija Kostić, J. Gržinić, E. Pap, M. Petković, Ana Blagojević, S. Stanišić, Jelena Teodorović, Slađana Čabrilo\",\"doi\":\"10.15308/SINTEZA-2019-388-393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a model for constructing a data set aimed at predicting a price of a real estate (houses and flats) from the standard Internet ads. 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Construction of Training Data for Price Prediction of a Real Estate from Internet Ads
The paper presents a model for constructing a data set aimed at predicting a price of a real estate (houses and flats) from the standard Internet ads. The model for predicting a real estate price includes, in addition to standard real estate's features (area, number of bedrooms, etc.) appearing in ad, attractiveness of a real estate location as well as information on some additional interior facilities (e.g., refrigerator, dish-washing machine, stove, etc.). The proposed training set construction model uses OpenStreetMap's Overpass API for determining attractiveness of a real estate's location, and a convolution neural network for detecting interior facilities from real estate photos.
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