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- Publisher Website: 10.1145/3132847.3133073
- Scopus: eid_2-s2.0-85037362074
- WOS: WOS:000440845300248
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Conference Paper: SEQ: Example-based Query for Spatial Objects
Title | SEQ: Example-based Query for Spatial Objects |
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Authors | |
Issue Date | 2017 |
Publisher | ACM. |
Citation | The 2017 ACM on Conference on Information and Knowledge Management, Singapore, 6-10 November 2017. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017, p. 2179-2182 How to Cite? |
Abstract | Spatial object search is prevalent in map services (e.g., Google Maps). To rent an apartment, for example, one will take into account its nearby facilities, such as supermarkets, hospitals, and subway stations. Traditional keyword search solutions, such as the nearby function in Google Maps, are insufficient in expressing the often complex attribute/spatial requirements of users. Those require- ments, however, are essential to reflect the user search intention. In this paper, we propose the Spatial Exemplar Query (SEQ), which allows the user to input a result example over an interface inside the map service. We then propose an effective similarity measure to evaluate the proximity between a candidate answer and the given example. We conduct a user study to validate the effectiveness of SEQ. Our result shows that more than 88% of users would like to have an example assisted search in map services. Moreover, SEQ gets a user satisfactory score of 4.3/5.0, which is more than 2 times higher than that of a baseline solution. |
Persistent Identifier | http://hdl.handle.net/10722/243247 |
ISBN | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Luo, S | - |
dc.contributor.author | Hu, J | - |
dc.contributor.author | Cheng, CK | - |
dc.contributor.author | Yang, J | - |
dc.contributor.author | Kao, CM | - |
dc.date.accessioned | 2017-08-25T02:52:11Z | - |
dc.date.available | 2017-08-25T02:52:11Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | The 2017 ACM on Conference on Information and Knowledge Management, Singapore, 6-10 November 2017. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017, p. 2179-2182 | - |
dc.identifier.isbn | 978-1-4503-4918-5 | - |
dc.identifier.uri | http://hdl.handle.net/10722/243247 | - |
dc.description.abstract | Spatial object search is prevalent in map services (e.g., Google Maps). To rent an apartment, for example, one will take into account its nearby facilities, such as supermarkets, hospitals, and subway stations. Traditional keyword search solutions, such as the nearby function in Google Maps, are insufficient in expressing the often complex attribute/spatial requirements of users. Those require- ments, however, are essential to reflect the user search intention. In this paper, we propose the Spatial Exemplar Query (SEQ), which allows the user to input a result example over an interface inside the map service. We then propose an effective similarity measure to evaluate the proximity between a candidate answer and the given example. We conduct a user study to validate the effectiveness of SEQ. Our result shows that more than 88% of users would like to have an example assisted search in map services. Moreover, SEQ gets a user satisfactory score of 4.3/5.0, which is more than 2 times higher than that of a baseline solution. | - |
dc.language | eng | - |
dc.publisher | ACM. | - |
dc.relation.ispartof | Proceedings of the 2017 ACM on Conference on Information and Knowledge Management | - |
dc.title | SEQ: Example-based Query for Spatial Objects | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Cheng, CK: ckcheng@cs.hku.hk | - |
dc.identifier.email | Kao, CM: kao@cs.hku.hk | - |
dc.identifier.authority | Cheng, CK=rp00074 | - |
dc.identifier.authority | Kao, CM=rp00123 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1145/3132847.3133073 | - |
dc.identifier.scopus | eid_2-s2.0-85037362074 | - |
dc.identifier.hkuros | 275518 | - |
dc.identifier.spage | 2179 | - |
dc.identifier.epage | 2182 | - |
dc.identifier.isi | WOS:000440845300248 | - |
dc.publisher.place | New York, NY | - |