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| Content Provider | ACM Digital Library |
|---|---|
| Author | Imbe, Takuo Ishibashi, Shuichi Sato, Chihiro İnami, Masahiko Takeuchi, Shigeyuki Okude, Naohito Inakage, Masa |
| Abstract | Recommendation systems have become widespread, however these systems only determine information inputted from the customers through a browser, and cannot be used when actually moving around outside. This paper presents TTI Model, a model extracting individual's curiosity level in urban spaces on their spare time by collecting behavior data from sensors. It calculates person's real time curiosity level by analyzing behavior depending on the walking speed within the city, such as window shopping or just hanging around by themselves. This paper evaluates this model with a sensor device prototype, and elaborates possibilities when understanding individuals in detail, by extracting the curiosity predicted from current behaviors using sensors. |
| Starting Page | 352 |
| Ending Page | 355 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450301039 |
| DOI | 10.1145/1858171.1858235 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-08-16 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Curiosity Urban experience User analysis Bayesian networks |
| Content Type | Text |
| Resource Type | Article |
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