Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup

Detalhes bibliográficos
Autor(a) principal: Dobreva, Maria Lubomirova
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/91224
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
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spelling Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startupReal EstatePredictive modelData miningDays on marketLASSO regressionProject Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThis is a research project for applying data mining techniques on Real Estate data in cooperation with Homeheed, a startup in the area of real estate, providing a platform solution as a single source of truth in Sofia, Bulgaria. This project suggests the development of a predictive model by using LASSO regression with the premise to determine days on market. As a consequence, the discoveries are expected to contribute to the Startup by providing insights about more attractive listings, and so will support faster return on investment. Additionally, the paper provides an experimental part where misleading and fake listings are targeted in order to support fraud and real availability of a listing detection. The project’s main objectives and assumptions are that advanced statistics and information management can build such a synergy with data and business models that allows enhancement of both market entry strategy and quality of service.Henriques, Roberto André PereiraCastelli, MauroRUNDobreva, Maria Lubomirova2020-01-15T16:06:21Z2019-12-182019-12-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/91224TID:202366570enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:40:32Zoai:run.unl.pt:10362/91224Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:37:18.104950Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
title Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
spellingShingle Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
Dobreva, Maria Lubomirova
Real Estate
Predictive model
Data mining
Days on market
LASSO regression
title_short Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
title_full Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
title_fullStr Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
title_full_unstemmed Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
title_sort Data-driven evaluation of real estate liquidity : predicting days on market to optimize the sales strategy of a startup
author Dobreva, Maria Lubomirova
author_facet Dobreva, Maria Lubomirova
author_role author
dc.contributor.none.fl_str_mv Henriques, Roberto André Pereira
Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Dobreva, Maria Lubomirova
dc.subject.por.fl_str_mv Real Estate
Predictive model
Data mining
Days on market
LASSO regression
topic Real Estate
Predictive model
Data mining
Days on market
LASSO regression
description Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies Management
publishDate 2019
dc.date.none.fl_str_mv 2019-12-18
2019-12-18T00:00:00Z
2020-01-15T16:06:21Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/91224
TID:202366570
url http://hdl.handle.net/10362/91224
identifier_str_mv TID:202366570
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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