Abstract
With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.
| Original language | English |
|---|---|
| Title of host publication | Databases Theory and Applications |
| Subtitle of host publication | 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings |
| Editors | Junhu Wang, Gao Cong, Jinjun Chen, Jianzhong Qi |
| Place of Publication | Cham Switzerland |
| Publisher | Springer |
| Pages | 53-67 |
| Number of pages | 15 |
| ISBN (Electronic) | 9783319920139 |
| ISBN (Print) | 9783319920122 |
| DOIs | |
| Publication status | Published - 1 Jan 2018 |
| Event | Australasian Database Conference 2018 - Griffith University, Gold Coast, Australia Duration: 23 May 2018 → 25 May 2018 Conference number: 23rd http://www.ict.griffith.edu.au/conferences/adc2018/ |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 10837 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | Australasian Database Conference 2018 |
|---|---|
| Abbreviated title | ADC 2018 |
| Country | Australia |
| City | Gold Coast |
| Period | 23/05/18 → 25/05/18 |
| Internet address |
Cite this
}
Location-aware group preference queries in social-networks. / Sohail, Ammar; Hidayat, Arif; Cheema, Muhammad Aamir; Taniar, David.
Databases Theory and Applications: 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings. ed. / Junhu Wang; Gao Cong; Jinjun Chen; Jianzhong Qi. Cham Switzerland : Springer, 2018. p. 53-67 (Lecture Notes in Computer Science; Vol. 10837).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Location-aware group preference queries in social-networks
AU - Sohail, Ammar
AU - Hidayat, Arif
AU - Cheema, Muhammad Aamir
AU - Taniar, David
PY - 2018/1/1
Y1 - 2018/1/1
N2 - With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.
AB - With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Topk) query. For a group of users, a SG-Topk query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.
UR - http://www.scopus.com/inward/record.url?scp=85047924155&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-92013-9_5
DO - 10.1007/978-3-319-92013-9_5
M3 - Conference Paper
SN - 9783319920122
T3 - Lecture Notes in Computer Science
SP - 53
EP - 67
BT - Databases Theory and Applications
A2 - Wang, Junhu
A2 - Cong, Gao
A2 - Chen, Jinjun
A2 - Qi, Jianzhong
PB - Springer
CY - Cham Switzerland
ER -