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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >
Search as if You were in Your Home Town : Geographic Search by Regional Context and Dynamic Feature-space Selection
| Title: | Search as if You were in Your Home Town : Geographic Search by Regional Context and Dynamic Feature-space Selection |
| Authors: | Kato, Makoto P Browse this author | | Ohshima, Hiroaki Browse this author →KAKEN DB | | Oyama, Satoshi Browse this author →KAKEN DB | | Tanaka, Katsumi Browse this author →KAKEN DB |
| Keywords: | Geographic search | | query-by-example | | dynamic feature-space | | heterogeneous domains |
| Issue Date: | 2010 |
| Publisher: | ACM |
| Citation: | CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management, ISBN: 978-1-4503-0099-5 |
| Start Page: | 1541 |
| End Page: | 1544 |
| Publisher DOI: | 10.1145/1871437.1871667 |
| Abstract: | We propose a query-by-example geographic object search method for users that do not know well about the place they are in. Geographic objects, such as restaurants, are often retrieved using an attribute-based or keyword query. These methods, however, are dif- ficult to use for users that have little knowledge on the place where they want to search. The proposed query-by-example method allows users to query by selecting examples in familiar places for retrieving objects in unfamiliar places. One of the challenges is to predict an effective distance metric, which varies for individuals. Another challenge is to calculate the distance between objects in heterogeneous domains considering the feature gap between them, for example, restaurants in Japan and China. Our proposed method is used to robustly estimate the distance metric by amplifying the difference between selected and non-selected examples. By using the distance metric, each object in a familiar domain is evenly assigned to one in an unfamiliar domain to eliminate the difference between those domains. We developed a restaurant search using data obtained from a Japanese restaurant Web guide to evaluate our method. |
| Conference Name: | ACM international conference on Information and knowledge management (CIKM '10) |
| Conference Sequence: | 19 |
| Conference Place: | Toronto, ON |
| Rights: | ©2010 ACM. This is the author’s version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management, ISBN: 978-1-4503-0099-5, 2010 http://doi.acm.org/10.1145/1871437.1871667 |
| Type: | proceedings (author version) |
| URI: | http://hdl.handle.net/2115/65276 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 小山 聡
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