| Presentation | 2014-06-14 On-site likelihood identification of tweets with context information Yurie ONITSUKA, Kazutaka SHIMADA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The Web contains much information for the tourism, such as impressions and sentiments about sightseeing areas. Analyzing the information is a significant task for tourism informatics. A useful target resource for the analysis is information on Twitter. However, all tweets with keywords, which are related to facilities and events for tourism, might be not tourism information. In this paper, we propose a method for estimating on-site likelihood of tweets. The task is to identify whether each tweet has high on-site likelihood. We introduce a filtering process and a machine learning technique for the task. In addition, we apply previous and next tweets for the identification task, as context information. Experimental results show the effectiveness of the combination method and context information. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Twitter / Context / On-site likelihood |
| Paper # | NLC2014-5 |
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| Conference Information | |
| Committee | NLC |
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| Conference Date | 2014/6/7(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Natural Language Understanding and Models of Communication (NLC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | On-site likelihood identification of tweets with context information |
| Sub Title (in English) | |
| Keyword(1) | |
| Keyword(2) | Context |
| Keyword(3) | On-site likelihood |
| 1st Author's Name | Yurie ONITSUKA |
| 1st Author's Affiliation | Department of Artificial Intelligence, Kyushu Institute of Technology() |
| 2nd Author's Name | Kazutaka SHIMADA |
| 2nd Author's Affiliation | Department of Artificial Intelligence, Kyushu Institute of Technology |
| Date | 2014-06-14 |
| Paper # | NLC2014-5 |
| Volume (vol) | vol.114 |
| Number (no) | 81 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |