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 article describes how to build a property search behavior corpus derived from microblogging timelines, in which tweets related to property search are annotated. We applied microtask-based crowdsourcing to tweet data, and build a corpus which consists of timelines of specific users which are annotated with property search stages (e.g. gathering of property information, and property preview). As a result, property search processes by tens of people were annotated. This corpus is intended to use for redesigning property information services, and marketing information services for potential users.
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 article describes how to build a property search behavior corpus derived from microblogging timelines, in which tweets related to property search are annotated. We applied microtask-based crowdsourcing to tweet data, and build a corpus which consists of timelines of specific users which are annotated with property search stages (e.g. gathering of property information, and property preview). As a result, property search processes by tens of people were annotated. This corpus is intended to use for redesigning property information services, and marketing information services for potential users.
15. ᢤ⢋
(Wikipedia᪥ᮏㄒ∧,
2014/09/01
09:00ࠥ10:00
JST)
ja
䝕䞁䜾⇕㻌㻌㻌㻌㻌㻌㻌㻌10745
554450816
ja
䝯䜲䞁䝨䞊䝆㻌㻌㻌㻌14093
438162758
ja
㛵ᮾ㟈⅏㻌㻌㻌㻌㻌㻌3114
281205408
ja
9᭶1᪥㻌㻌1833
165384461
ja
24㛫䝔䝺䝡_䛂ឡ䛿ᆅ⌫䜢ᩆ䛖䛃㻌1723
137958282
ja
䜲䝏䝻䞊㻌㻌㻌㻌㻌㻌㻌㻌192
120358324
ja
ᮾ᪥ᮏ㟈⅏㻌㻌㻌㻌437
110995792
ja
ྜྷỌᑠⓒྜ㻌㻌㻌㻌㻌㻌2284
86710534
ja
䝪䝹䝅䜰䞉䝗䝹䝖䝮䞁䝖㻌㻌1388
75815693
ja
㯮⏣Ꮥ㧗㻌㻌㻌㻌㻌㻌㻌㻌1168
71345773
ja
ⰼᏊ䛸䜰䞁㻌㻌㻌㻌㻌㻌877
67992101
ja
ᇛᓥⱱ㻌㻌2197
55590788
ja
᪂ୡ⣖䜶䞂䜯䞁䝀䝸䜸䞁㻌㻌415
55537912
ja
㜵⅏䛾᪥㻌㻌㻌㻌㻌㻌㻌㻌4493
55510476
ja
ᑠῲඃᏊ㻌㻌㻌㻌㻌㻌㻌㻌2751
52931239
ja
ゟሗ_2014ᖺ㻌㻌㻌㻌㻌111
52488871
ja
㜰⚄䞉ῐ㊰㟈⅏㻌㻌㻌㻌㻌㻌㻌㻌285
52182898