Selection of housing, one of the necessities of human life, has a great influence on life for a long time. However, since it requires a wide range of information gathering and consideration before decision, state-of-the-art recommendation algorithms such as collaborative filtering do not work well. In this presentation, after reviewing issues specific to the real estate field, I cited examples of "application of crowdsourcing to social media (Twitter timelines)" and "application of deep learning to property images" as an effort by our research group. Finally I discuss what kind of AI technology is applicable in the real estate field.
Mining User Experience through Crowdsourcing: A Property Search Behavior Corp...Yoji Kiyota
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This document describes a study that aimed to establish a method for understanding user experiences in property searching through analyzing Twitter timelines. The researchers collected Twitter timelines of followers of a Japanese property search service account and used crowdsourcing microtasks to extract tweets related to property searching and analyze them based on a conventional property search process framework. Workers were asked to categorize timeline fragments as either related or unrelated to property searching. This allowed the researchers to build a corpus of property search behavior data derived from social media for analyzing user needs and experiences.
Selection of housing, one of the necessities of human life, has a great influence on life for a long time. However, since it requires a wide range of information gathering and consideration before decision, state-of-the-art recommendation algorithms such as collaborative filtering do not work well. In this presentation, after reviewing issues specific to the real estate field, I cited examples of "application of crowdsourcing to social media (Twitter timelines)" and "application of deep learning to property images" as an effort by our research group. Finally I discuss what kind of AI technology is applicable in the real estate field.
Mining User Experience through Crowdsourcing: A Property Search Behavior Corp...Yoji Kiyota
?
This document describes a study that aimed to establish a method for understanding user experiences in property searching through analyzing Twitter timelines. The researchers collected Twitter timelines of followers of a Japanese property search service account and used crowdsourcing microtasks to extract tweets related to property searching and analyze them based on a conventional property search process framework. Workers were asked to categorize timeline fragments as either related or unrelated to property searching. This allowed the researchers to build a corpus of property search behavior data derived from social media for analyzing user needs and experiences.
1. 第 1 0 回 A R G W I 2 研 究 会 技 術 報 告 ( 2 0 1 7 . 0 7 . 0 7 )
LIFEをFULLにする研究とは?
?「介護」「不動産」を例として?
LIF ULL Lab 主席研究員
清田 陽司
2 0 1 7 . 0 7 . 0 7 第 1 0 回 A R G W e b イ ン テ リ ジ ェ ン ス と イ ン タ ラ ク シ ョ ン 研 究 会 ( W I 2 研 究 会 )
於 京 都 大 学 百 周 年 時 計 台 記 念 館
C o p y r i g h t ? L I F U L L A l l R i g h t s R e s e r v e d .
2. 第 1 0 回 A R G W I 2 研 究 会 技 術 報 告 ( 2 0 1 7 . 0 7 . 0 7 )
社名?ブランド名の変更
(2017.04.01)
3. 第 1 0 回 A R G W I 2 研 究 会 技 術 報 告 ( 2 0 1 7 . 0 7 . 0 7 )