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- Publisher Website: 10.1109/SmartCity.2015.40
- Scopus: eid_2-s2.0-84973901456
- WOS: WOS:000392313100003
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Conference Paper: On interesting place finding in social sensing: An emerging smart city application paradigm
Title | On interesting place finding in social sensing: An emerging smart city application paradigm |
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Authors | |
Keywords | Interesting Place Finding Maximum Likelihood Estimation Smart City Social Sensing |
Issue Date | 2015 |
Citation | Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015, 2015, p. 13-20 How to Cite? |
Abstract | Social sensing has emerged as a new application paradigm for smart cities where a crowd of social sources (humans or devices on their behalf) collectively contribute a large amount of observations about the physical world. This paper focuses on an interesting place finding problem in social sensing where the goal is to accurately identify the interesting places in a city where people may have strong interests to visit (e.g., parks, museums, historic sites, scenic trails, etc.). Solving this problem is not trivial because (i) many interesting places are not necessarily frequently visited by the average people and hence less likely to be found by the traditional recommendation systems, (ii) the user's social connections could directly affect their visiting behavior and the interestingness judgment of a given place. In this paper, we develop a new Social-aware Interesting Place Finding (SIPF) approach that solves the above problem by explicitly incorporating both the user's travel experience and social relationship into a rigorous analytical framework. The evaluation results showed that the new approach significantly outperforms the state-of-the-arts using two real-world datasets collected from location-based social network service. |
Persistent Identifier | http://hdl.handle.net/10722/308908 |
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 | 2021-12-08T07:50:23Z | - |
dc.date.available | 2021-12-08T07:50:23Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015, 2015, p. 13-20 | - |
dc.identifier.uri | http://hdl.handle.net/10722/308908 | - |
dc.description.abstract | Social sensing has emerged as a new application paradigm for smart cities where a crowd of social sources (humans or devices on their behalf) collectively contribute a large amount of observations about the physical world. This paper focuses on an interesting place finding problem in social sensing where the goal is to accurately identify the interesting places in a city where people may have strong interests to visit (e.g., parks, museums, historic sites, scenic trails, etc.). Solving this problem is not trivial because (i) many interesting places are not necessarily frequently visited by the average people and hence less likely to be found by the traditional recommendation systems, (ii) the user's social connections could directly affect their visiting behavior and the interestingness judgment of a given place. In this paper, we develop a new Social-aware Interesting Place Finding (SIPF) approach that solves the above problem by explicitly incorporating both the user's travel experience and social relationship into a rigorous analytical framework. The evaluation results showed that the new approach significantly outperforms the state-of-the-arts using two real-world datasets collected from location-based social network service. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015 | - |
dc.subject | Interesting Place Finding | - |
dc.subject | Maximum Likelihood Estimation | - |
dc.subject | Smart City | - |
dc.subject | Social Sensing | - |
dc.title | On interesting place finding in social sensing: An emerging smart city application paradigm | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/SmartCity.2015.40 | - |
dc.identifier.scopus | eid_2-s2.0-84973901456 | - |
dc.identifier.spage | 13 | - |
dc.identifier.epage | 20 | - |
dc.identifier.isi | WOS:000392313100003 | - |