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DC Field | Value | Language |
---|---|---|
dc.citation.conferencePlace | US | - |
dc.citation.conferencePlace | Portland | - |
dc.citation.endPage | 2209 | - |
dc.citation.startPage | 2199 | - |
dc.citation.title | ACM SIGMOD International Conference on Management of Data | - |
dc.contributor.author | Kim, Junghoon | - |
dc.contributor.author | Guo, T. | - |
dc.contributor.author | Feng, K. | - |
dc.contributor.author | Cong, G. | - |
dc.contributor.author | Khan, A. | - |
dc.contributor.author | Choudhury, F.M. | - |
dc.date.accessioned | 2024-01-31T23:06:43Z | - |
dc.date.available | 2024-01-31T23:06:43Z | - |
dc.date.created | 2022-09-08 | - |
dc.date.issued | 2020-06-14 | - |
dc.description.abstract | Searching for a community based on query nodes in a graph is a fundamental problem and has been extensively investigated. Most of the existing approaches focus on finding a community in a social network, and very few studies consider location-based social networks where users can check in locations. In this paper we propose the GeoSocial Community Search problem (GCS) which aims to find a social community and a cluster of spatial locations that are densely connected in a location-based social network simultaneously. The GCS can be useful for marketing and user/location recommendation. To the best of our knowledge, this is the first work to find a social community and a cluster of spatial locations that are densely connected from location-based social networks. We prove that the problem is NP-hard, and is not in APX, unless P = NP. To solve this problem, we propose three algorithms: core-based basic algorithm, top-down greedy removing algorithm, and an expansion algorithm. Finally, we report extensive experimental studies that offer insights into the efficiency and effectiveness of the proposed solutions. | - |
dc.identifier.bibliographicCitation | ACM SIGMOD International Conference on Management of Data, pp.2199 - 2209 | - |
dc.identifier.doi | 10.1145/3318464.3380603 | - |
dc.identifier.issn | 0730-8078 | - |
dc.identifier.scopusid | 2-s2.0-85086235528 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/78490 | - |
dc.language | 영어 | - |
dc.publisher | Association for Computing Machinery | - |
dc.title | Densely Connected User Community and Location Cluster Search in Location-Based Social Networks | - |
dc.type | Conference Paper | - |
dc.date.conferenceDate | 2020-06-14 | - |
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