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Roadscape-based Route Recommender System Using Coarse-to-fine Route Search
https://ipsj.ixsq.nii.ac.jp/records/195466
https://ipsj.ixsq.nii.ac.jp/records/195466d3167c84-fa6a-4054-9643-1092cd39cd2c
| 名前 / ファイル | ライセンス | アクション |
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IPSJ-TOD1202002.pdf (9.4 MB)
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Copyright (c) 2019 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Trans(1) | |||||||||
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| 公開日 | 2019-04-11 | |||||||||
| タイトル | ||||||||||
| タイトル | Roadscape-based Route Recommender System Using Coarse-to-fine Route Search | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | Roadscape-based Route Recommender System Using Coarse-to-fine Route Search | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | [研究論文] route recommender system, route search, roadscape | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者所属 | ||||||||||
| Ryukoku University | ||||||||||
| 著者所属 | ||||||||||
| Ryukoku University | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Ryukoku University | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Ryukoku University | ||||||||||
| 著者名 |
Koji, Kawamata
× Koji, Kawamata
× Kenta, Oku
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| 著者名(英) |
Koji, Kawamata
× Koji, Kawamata
× Kenta, Oku
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | We propose Roadscape-based Route Recommender System (R3), which provides diversified roadscape-based routes. Given starting and destination points, R3 provides four types of roadscape-based routes: rural-, mountainous-, waterside-, and urban-prior routes. To reduce the computational cost, we propose a coarse-to-fine route search approach that consists of a roadscape-based clustering method, roadscape cluster graph, coarse-grained route search, and fine-grained route search. We evaluated the performance of R3 using network data for real roads. The experimental results qualitatively show the validity of the generated roadscape clusters by comparing them with Google satellite maps and Google Street View images. The results also show the validity of the roadscape-based route recommendations. Furthermore, the results show that using a coarse-grained route search can significantly reduce the route search time. Finally, we quantitatively evaluate R3 from the perspective of users. The results show that R3 can appropriately recommend roadscape-based routes for given scenarios. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.27(2019) (online) ------------------------------ |
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| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | We propose Roadscape-based Route Recommender System (R3), which provides diversified roadscape-based routes. Given starting and destination points, R3 provides four types of roadscape-based routes: rural-, mountainous-, waterside-, and urban-prior routes. To reduce the computational cost, we propose a coarse-to-fine route search approach that consists of a roadscape-based clustering method, roadscape cluster graph, coarse-grained route search, and fine-grained route search. We evaluated the performance of R3 using network data for real roads. The experimental results qualitatively show the validity of the generated roadscape clusters by comparing them with Google satellite maps and Google Street View images. The results also show the validity of the roadscape-based route recommendations. Furthermore, the results show that using a coarse-grained route search can significantly reduce the route search time. Finally, we quantitatively evaluate R3 from the perspective of users. The results show that R3 can appropriately recommend roadscape-based routes for given scenarios. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.27(2019) (online) ------------------------------ |
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| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AA11464847 | |||||||||
| 書誌情報 |
情報処理学会論文誌データベース（TOD） 巻 12, 号 2, 発行日 2019-04-11 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 1882-7799 | |||||||||
| 出版者 | ||||||||||
| 言語 | ja | |||||||||
| 出版者 | 情報処理学会 | |||||||||
