article

Mobility and social networking: a data management perspective

Authors:

Mohamed F. Mokbel,

Mohamed SarwatAuthors Info & Claims

Proceedings of the VLDB Endowment, Volume 6, Issue 11

Pages 1196 - 1197

https://doi.org/10.14778/2536222.2536257

Published: 01 August 2013 Publication History

Abstract

This tutorial presents the state-of-the-art research that lies at the intersection of two hot topics in the data management community: (1) social networking and (2) mobility. In this tutorial, we give an overview of existing research work, systems, and applications related to both social networking and mobility. In addition, we introduce several resources (i.e., datasets, software tools) as well as a list of promising research directions.

References

[1]

J. Bao, M. F. Mokbel, and C.-Y. Chow. GeoFeed: A Location-Aware News Feed System. In ICDE, 2012.

[2]

S. Bhagat, A. Goyal, and L. V. S. Lakshmanan. Maximizing product adoption in social networks. In WSDM, 2012.

[3]

M. Busch, K. Gade, B. Larson, P. Lok, S. Luckenbill, and J. Lin. Earlybird: Real-Time Search at Twitter. In ICDE, 2012.

[4]

Y. Cai and T. Xu. Design, analysis, and implementation of a large-scale real-time location-based information sharing system. In MobiSys, 2008.

[5]

C. C. CAO, J. She, Y. Tong, and L. Chen. Whom to ask? jury selection for decision making tasks on micro-blog services. In VLDB, 2012.

[6]

C. Chen, F. Li, B. C. Ooi, and S. Wu. Ti: an efficient indexing mechanism for real-time search on tweets. In SIGMOD, 2011.

[7]

L. Chen, G. Cong, C. S. Jensen, and D. Wu. Spatial Keyword Query Processing: An Experimental Evaluation. In VLDB, 2013.

[8]

Y. Chen, K. Jiang, Y. Zheng, C. Li, and N. Yu. Trajectory simplification method for location-based social networking services. In GIS-LBSN, 2009.

[9]

E. Cho, S. A. Myers, and J. Leskovec. Friendship and mobility: user movement in location-based social networks. In KDD, 2011.

[10]

A. Efentakis, D. Theodorakis, and D. Pfoser. Crowdsourcing computing resources for shortest-path computation. In GIS, 2012.

[11]

A. Feng, M. J. Franklin, D. Kossmann, T. Kraska, S. Madden, S. Ramesh, A. Wang, and R. Xin. CrowdDB: Query Processing with the VLDB Crowd. PVLDB, 2011.

[12]

D. Freni, C. R. Vicente, S. Mascetti, C. Bettini, and C. S. Jensen. Preserving location and absence privacy in geo-social networks. In CIKM, 2010.

[13]

N. Gupta, L. Kot, S. Roy, G. Bender, J. Gehrke, and C. Koch. Entangled queries: Enabling declarative data-driven coordination. TODS, 37(3):21, 2012.

[14]

L. Kazemi and C. Shahabi. Geocrowd: Enabling query answering with spatial crowdsourcing. In GIS, 2012.

[15]

A. Kittur, E. H. Chi, and B. Suh. Crowdsourcing user studies with mechanical turk. In CHI, 2008.

[16]

K. Kodama, Y. Iijima, X. Guo, and Y. Ishikawa. Skyline queries based on user locations and preferences for making location-based recommendations. In GIS-LBSN, 2009.

[17]

J. J. Levandoski, M. Sarwat, A. Eldawy, and M. F. Mokbel. LARS: A Location-Aware Recommender System. In ICDE, 2012.

[18]

M. D. Lieberman and H. Samet. Supporting rapid processing and interactive map-based exploration of streaming news. In GIS, 2012.

[19]

W. Lu and L. V. S. Lakshmanan. Profit maximization over social networks. In ICDM, 2012.

[20]

W. Lu, Y. Shen, S. Chen, and B. C. Ooi. Efficient processing of k nearest neighbor joins using mapreduce. In VLDB, 2012.

[21]

K. Mamouras, S. Oren, L. Seeman, L. Kot, and J. Gehrke. The Complexity of Social Coordination. PVLDB, 5(11):1172-1183, 2012.

[22]

A. Marcus, M. S. Bernstein, O. Badar, D. R. Karger, S. Madden, and R. C. Miller. Tweets as data: demonstration of TweeQL and Twitinfo. In SIGMOD, 2011.

[23]

G. D. F. Morales, A. Gionis, and M. Sozio. Social content matching in mapreduce. In VLDB, 2011.

[24]

A. G. Parameswaran, H. Garcia-Molina, H. Park, N. Polyzotis, A. Ramesh, and J. Widom. CrowdScreen: algorithms for filtering data with humans. In SIGMOD, pages 361-372, 2012.

[25]

A. G. Parameswaran, H. Park, H. Garcia-Molina, N. Polyzotis, and J. Widom. Deco: declarative crowdsourcing. In CIKM, 2012.

[26]

H. Park, R. Pang, A. G. Parameswaran, H. Garcia-Molina, N. Polyzotis, and J. Widom. An overview of the deco system: data model and query language; query processing and optimization. SIGMOD Record, 41(4):22-27, 2012.

[27]

H. Park, R. Pang, A. G. Parameswaran, H. Garcia-Molina, N. Polyzotis, and J. Widom. Deco: A System for Declarative Crowdsourcing. PVLDB, 5(12):1990-1993, 2012.

[28]

M.-H. Park et al. Location-based recommendation system using bayesian user's preference model in mobile devices. In UIC, 2007.

[29]

K. P. N. Puttaswamy and B. Y. Zhao. Preserving privacy in location-based mobile social applications. In HotMobile, 2010.

[30]

S. B. Roy and K. Chakrabarti. Location-aware type ahead search on spatial databases: semantics and efficiency. In SIGMOD, 2011.

[31]

S. B. Roy et al. Space efficiency in group recommendation. VLDB J., 19(6):877-900, 2010.

[32]

A. D. Sarma, H. Lee, H. Gonzalez, J. Madhavan, and A. Y. Halevy. Efficient spatial sampling of large geographical tables. In SIGMOD, 2012.

[33]

M. Sarwat, J. Bao, A. Eldawy, J. J. Levandoski, A. Magdy, and M. F. Mokbel. Sindbad: A Location-based Social Networking System. In SIGMOD, 2012.

[34]

M. Sarwat, J. J. Levandoski, A. Eldawy, and M. F. Mokbel. LARS*: A Scalable and Efficient Location-Aware Recommender System. In TKDE, 2013.

[35]

A. Silberstein, J. Terrace, B. F. Cooper, and R. Ramakrishnan. Feeding frenzy: Selectively materializing user's event feed. In SIGMOD, 2010.

[36]

Y. Takeuchi and M. Sugimoto. An outdoor recommendation system based on user location history. In UIC, 2006.

[37]

S. Thirumuruganathan, M. Das, S. Desai, S. Amer-Yahia, G. Das, and C. Yu. MapRat: Meaningful Explanation, Interactive Exploration and Geo-Visualization of Collaborative Ratings. PVLDB, 5(12):1986-1989, 2012.

[38]

J. R. Thomsen, M. L. Yiu, and C. S. Jensen. Effective caching of shortest paths for location-based services. In SIGMOD, 2012.

[39]

P. Venetis, H. Gonzalez, C. S. Jensen, and A. Y. Halevy. Hyper-local, directions-based ranking of places. VLDB, 4(5):290-301, 2011.

[40]

W. Wei, F. Xu, and Q. Li. MobiShare: Flexible privacy-preserving location sharing in mobile online social networks. In INFOCOM, 2012.

[41]

W. Xu, C.-Y. Chow, M. L. Yiu, Q. Li, and C. K. Poon. MobiFeed: a location-aware news feed system for mobile users. In GIS, 2012.

[42]

M. Ye, P. Yin, and W.-C. Lee. Location recommendation for location-based social networks. In GIS, 2010.

[43]

H. Yin, B. Cui, J. Li, J. Yao, and C. Chen. Challenging the Long Tail Recommendation. PVLDB, 5(9):896-907, 2012.

[44]

C. Zhang, L. Shou, K. Chen, G. Chen, and Y. Bei. Evaluating geo-social influence in location-based social networks. In CIKM, 2012.

[45]

V. Zheng, Y. Zheng, X. Xie, and Q. Yang. Collaborative Location and Activity Recommendations with GPS History Data. In WWW, 2010.

[46]

Y. Zheng, Y. Chen, X. Xie, and W.-Y. Ma. Geolife2.0: A location-based social networking service. In MDM, 2009.

[47]

Y. Zheng and X. Xie. Learning travel recommendations from user-generated GPS traces. ACM Transactions on Intelligent Systems and Technology (TIST), 2(1):2, 2011.

[48]

Y. Zheng, X. Xie, and W.-Y. Ma. GeoLife: A Collaborative Social Networking Service among User, Location and Trajectory. IEEE Data Eng. Bull., 33(2):32-39, 2010.

Cited By

Grabovitch-Zuyev IKanza YKravi EPat BNascimento MRenz MEmrich TMouratidis KZüfle A(2014)On the Correlation Between Textual Content and Geospatial Locations in MicroblogsProceedings of Workshop on Managing and Mining Enriched Geo-Spatial Data10.1145/2619112.2619115(1-6)Online publication date: 22-Jun-2014
https://dl.acm.org/doi/10.1145/2619112.2619115

Index Terms

Mobility and social networking: a data management perspective
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Web-based interaction

Index terms have been assigned to the content through auto-classification.

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cover image Proceedings of the VLDB Endowment

Proceedings of the VLDB Endowment Volume 6, Issue 11

August 2013

237 pages

ISSN:2150-8097

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VLDB Endowment

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Published: 01 August 2013

Published in PVLDB Volume 6, Issue 11

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Cited By

Grabovitch-Zuyev IKanza YKravi EPat BNascimento MRenz MEmrich TMouratidis KZüfle A(2014)On the Correlation Between Textual Content and Geospatial Locations in MicroblogsProceedings of Workshop on Managing and Mining Enriched Geo-Spatial Data10.1145/2619112.2619115(1-6)Online publication date: 22-Jun-2014
https://dl.acm.org/doi/10.1145/2619112.2619115

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