Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
The VLDB Journal
Published in: The VLDB Journal 5/2017

19-07-2017 | Regular Paper

Geo-social group queries with minimum acquaintance constraints

Authors: Qijun Zhu, Haibo Hu, Cheng Xu, Jianliang Xu, Wang-Chien Lee

Published in: The VLDB Journal | Issue 5/2017

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The prosperity of location-based social networking has paved the way for new applications of group-based activity planning and marketing. While such applications heavily rely on geo-social group queries (GSGQs), existing studies fail to produce a cohesive group in terms of user acquaintance. In this paper, we propose a new family of GSGQs with minimum acquaintance constraints. They are more appealing to users as they guarantee a worst-case acquaintance level in the result group. For efficient processing of GSGQs on large location-based social networks, we devise two social-aware spatial index structures, namely SaR-tree and SaR*-tree. The latter improves on the former by considering both spatial and social distances when clustering objects. Based on SaR-tree and SaR*-tree, novel algorithms are developed to process various GSGQs. Extensive experiments on real datasets Gowalla and Twitter show that our proposed methods substantially outperform the baseline algorithms under various system settings.
previous article Query-aware locality-sensitive hashing scheme for norm
next article A distributed in-memory key-value store system on heterogeneous CPU–GPU cluster

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Footnotes
1
Such relation can be either a “friend” relation or a more intimate acquaintance relation, depending on the nature of the group event in a GSGQ service.
 
Literature
1.
Armenatzoglou, N., Papadopoulos, S., Papadias, D.: A general framework for geo-social query processing. In: Proceedings of VLDB (2013)
2.
Balasundaram, B., Butenko, S., Hicks, I.V.: Clique relaxations in social network analysis: the maximum k-plex problem. Oper. Res. 59(1), 133–142 (2011)
3.
Batagelj, V., Zaversnik, M.: An o(m) algorithm for cores decomposition of networks. In: CoRR (2003)
4.
Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: an efficient and robust access method for points and rectangles. In: Proceedings of SIGMOD (1990)
5.
Cao, X., Cong, G., Jensen, C.S., Ooi, B.C.: Collective spatial keyword querying. In SIGMOD Conference (2011)
6.
Cheng, J., Ke, Y., Chu, S., Ozsu, M.T.: Efficient core decomposition in massive networks. In: Proceedings of ICDE (2011)
7.
De Felipe, I., Hristidis, V., Rishe, N.: Keyword search on spatial databases. In Proceedings of ICDE (2008)
8.
Doytsher, Y., Galon, B., Kanza, Y.: Querying geo-social data by bridging spatial networks and social networks. In: ACM LBSN (2010)
9.
Faloutsos, C., McCurley, K., Tomkins, A.: Fast discovery of connection subgraphs. In KDD (2004)
10.
Finkel, R., Bentley, J.L.: Quad trees: a data structure for retrieval on composite keys. Acta Informatica 4(1), 1–9 (1974)
11.
12.
Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. In Proceedings of the National Academy of Sciences of the USA (2002)
13.
Guttman, A.: R-trees: a dynamic index structure for spatial searching. In Proceedings of SIGMOD (1984)
14.
Hao, F., Li, S., Min, G., Kim, H.-C., Yau, S.S., Yang L.T.: An efficient approach to generating location-sensitive recommendations in ad-hoc social network environments. IEEE Trans. Serv. Comput. 8(3), 520–533 (2015)
15.
Harary, F., Ross, I.C.: A procedure for clique detection using the group matrix. Sociometry 20(3), 205–215 (1957)
16.
Khalid, O., Khan, M.U.S., Khan, S.U., Zomaya, A.Y.: OmniSuggest: a ubiquitous cloud based context aware recommendation system for mobile social networks. IEEE Trans. Serv. Comput. 7(3), 401–414 (2014)
17.
Leskovec, J., Backstrom, L., Kumar, R., Tomkins, A.: Microscopic evolution of social networks. In KDD (2008)
18.
19.
Li, Y., Chen, R., Xu, J., Huang, Q., Hu, H., Choi, B.: Geo-social k-cover group queries for collaborative spatial computing. IEEE Trans. Knowl. Data Eng. (TKDE) 27(8), 2729–2742 (2015)CrossRef
20.
Liu, W., Sun, W., Chen, C., Huang, Y., Jing, Y., Chen, K.: Circle of friend query in geo-social networks. In DASFFA (2012)
21.
McClosky, B., Hicks, I.V.: Combinatorial algorithms for max k-plex. J. Combin. Optim. 23(1), 29–49 (2012)
22.
Moser, H., Niedermeier, R., Sorge,M.: Algorithms and experiments for clique relaxations-finding maximum s-plexes. In SEA (2009)
23.
Papadias, D., Shen, Q., Tao, Y., Mouratidis, K.: Group nearest neighbor queries. In ICDE (2004)
24.
25.
Seidman, S.B.: Network structure and minimum degree. Soc. Netw. 5(3), 269–287 (1983)
26.
Shi, J., Mamoulis, N., Wu, D., Cheung, D.W.: Density-based place clustering in geo-social networks. In Proceedings of ACM SIGMOD (2014)
27.
Shin, K., Eliassi-Rad, T., Faloutsos, C.: CoreScope: graph mining using k-core analysis—patterns, anomalies, and algorithms. In Proceedings of IEEE ICDE (2016)
28.
Sozio, M., Gionis, A.: The community-search problem and how to plan a successful cocktail party. In KDD (2010)
29.
Wu, D., Yiu, M.L., Jensen, C.S., Cong, G.: Efficient continuously moving top-k spatial keyword query processing. In Proceedings of ICDE (2011)
30.
Yang, D.-N., Chen, Y.-L., Lee, W.-C., Chen, M.-S.: On social-temporal group query with acquaintance constraint. In Proceedings of VLDB (2011)
31.
Yang, D.-N., Shen, C.-Y., Lee, W.-C., Chen, M.-S.: On socio-spatial group query for location-based social networks. In KDD (2012)
32.
Zhang, D., Chee, Y.M., Mondal, A., Tung, A.K.H., Kitsuregawa, M.: Keyword search in spatial databases: towards searching by document. In Proceedings of ICDE (2009)
33.
Zhang, J.-D., Chow, C.-Y., Li, Y.: iGeoRec: a personalized and efficient geographical location recommendation framework. IEEE Trans. Serv. Comput. 8(5), 701–714 (2015)
34.
Zhang, J.-D., Chow, C.-Y.: iGSLR: personalized geo-social location recommendation—a kernel density estimation approach. In Proceedings of ACM GIS (2013)
Metadata
Title
Geo-social group queries with minimum acquaintance constraints
Authors
Qijun Zhu
Haibo Hu
Cheng Xu
Jianliang Xu
Wang-Chien Lee
Publication date
19-07-2017
Publisher
Springer Berlin Heidelberg
Published in
The VLDB Journal / Issue 5/2017
Print ISSN: 1066-8888
Electronic ISSN: 0949-877X
DOI
https://doi.org/10.1007/s00778-017-0473-6

Other articles of this Issue 5/2017

The VLDB Journal 5/2017 Go to the issue

Regular Paper

A distributed in-memory key-value store system on heterogeneous CPU–GPU cluster

Regular Paper

Secret sharing for cloud data security: a survey

Regular Paper

Query-aware locality-sensitive hashing scheme for norm

Regular Paper

Graph repairing under neighborhood constraints

Regular Paper

Enhancing online video recommendation using social user interactions

Premium Partner

    Image Credits