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- Publisher Website: 10.1109/DCOSS.2016.12
- Scopus: eid_2-s2.0-84985916796
- WOS: WOS:000389774000009
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Conference Paper: Unsupervised interesting places discovery in location-based social sensing
Title | Unsupervised interesting places discovery in location-based social sensing |
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Authors | |
Keywords | Interesting place discovery Physical dependency Social dependency Social sensing Unsupervised learning |
Issue Date | 2016 |
Citation | Proceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016, 2016, p. 67-74 How to Cite? |
Abstract | This paper presents an unsupervised approach to accurately discover interesting places in a city from locationbased social sensing applications, a new sensing application paradigm that collects observations of physical world from Location-based Social Networks (LBSN). While there are a large amount of prior works on personalized Point of Interests (POI) recommendation systems, they used supervised learning approaches that did not work for users who have little or no historic (training) data. In this paper, we focused on an interesting place discovery problem where the goal is to accurately discover the interesting places in a city that average people may have strong interests to visit (e.g., parks, museums, historic sites, etc.) using unsupervised approaches. In particular, we develop a new Physical-Social-aware Interesting Place Discovery (PSIPD) scheme which jointly exploits the location's physical dependency and the visitor's social dependency to solve the interesting place discovery problem using an unsupervised approach. We compare our solution with state-ofthe- art baselines using two real world data traces from LBSN. The results showed that our approach achieved significant performance improvements compared to all baselines in terms of both estimation accuracy and ranking performance. |
Persistent Identifier | http://hdl.handle.net/10722/308921 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Huang, Chao | - |
dc.contributor.author | Wang, Dong | - |
dc.date.accessioned | 2021-12-08T07:50:24Z | - |
dc.date.available | 2021-12-08T07:50:24Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Proceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016, 2016, p. 67-74 | - |
dc.identifier.uri | http://hdl.handle.net/10722/308921 | - |
dc.description.abstract | This paper presents an unsupervised approach to accurately discover interesting places in a city from locationbased social sensing applications, a new sensing application paradigm that collects observations of physical world from Location-based Social Networks (LBSN). While there are a large amount of prior works on personalized Point of Interests (POI) recommendation systems, they used supervised learning approaches that did not work for users who have little or no historic (training) data. In this paper, we focused on an interesting place discovery problem where the goal is to accurately discover the interesting places in a city that average people may have strong interests to visit (e.g., parks, museums, historic sites, etc.) using unsupervised approaches. In particular, we develop a new Physical-Social-aware Interesting Place Discovery (PSIPD) scheme which jointly exploits the location's physical dependency and the visitor's social dependency to solve the interesting place discovery problem using an unsupervised approach. We compare our solution with state-ofthe- art baselines using two real world data traces from LBSN. The results showed that our approach achieved significant performance improvements compared to all baselines in terms of both estimation accuracy and ranking performance. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016 | - |
dc.subject | Interesting place discovery | - |
dc.subject | Physical dependency | - |
dc.subject | Social dependency | - |
dc.subject | Social sensing | - |
dc.subject | Unsupervised learning | - |
dc.title | Unsupervised interesting places discovery in location-based social sensing | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/DCOSS.2016.12 | - |
dc.identifier.scopus | eid_2-s2.0-84985916796 | - |
dc.identifier.spage | 67 | - |
dc.identifier.epage | 74 | - |
dc.identifier.isi | WOS:000389774000009 | - |