Abstract
Advancements in positioning techniques and mobile communications have enabled location-based services with a broad range of location-aware multimedia applications. Accordingly, various social multimedia data, relevant to different aspects of users’ daily life, is aggregated over time on the Internet. Such location-aware multimedia data contains rich context of users and has two implications: individual user interest and geographic-social behaviors. Exploiting these multimedia landscapes helps mine personal preferences, geographic interests and social connections, and brings the opportunities of discovering more interesting topics. In this chapter, we first introduce some examples of location-aware multimedia data and social interaction data. Then, we report some latest methods related to context detection and location-aware multimedia applications. We further present some analysis of geo-social data. Finally, we point out the trend in the integration of social and content delivery networks. In brief, this chapter delivers a picture of emerging geographic-aware multimedia technologies and applications, with location information as a clue.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Many social networking services allow users to self-report presence (known as check in) to a physical place and share their locations with their friends. Refer to http://en.wikipedia.org/wiki/Check-in.
- 2.
- 3.
Geo-tagging is the process of adding geographical identification metadata to various media data. Refer to http://en.wikipedia.org/wiki/Geotagging.
- 4.
- 5.
- 6.
- 7.
- 8.
References
Pallis G, Vakali A (2006) Insight and perspectives for content delivery networks. Commun ACM 49(1):101–106
Boyd DM, Ellison NB (2007) Social network sites: definition, history, and scholarship. J Comput-Mediat Commun 13(1):210–230
Junglas IA, Watson RT (2008) Location-based services. Commun ACM 51(3):65–69
Brodersen A, Scellato S, Wattenhofer M (2012) YouTube around the world: geographic popularity of videos. In: WWW’12, pp 241–250
Shen ZJ, Arslan Ay S, Kim SH, Zimmermann R (2011) Automatic tag generation and ranking for sensor-rich outdoor videos. In: ACM Multimedia’11, pp 93–102
Ma H, Zimmermann R, Kim SH (2012) HUGVid: handling, indexing and querying of uncertain geo-tagged videos. In: ACM SIGSPATIAL’12, pp 319–328
Yu Y, Shen, ZJ, Zimmermann R (2012) Automatic music soundtrack generation for outdoor videos from contextual sensor information. In: ACM Multimedia’12, pp 1377–1378
Shah RR, Yu Y, Zimmermann R (2014) User preference-aware music video generation based on modeling scene moods. In: ACM MMSys’14, pp 156–159
Shah RR, Yu Y, Zimmermann R (2014) ADVISOR-personalized video soundtrack recommendation by late fusion with heuristic rankings. In: ACM Multimedia’14
Bao J, Zheng Y, Mokbel MF (2012) Location-based and preference-aware recommendation using sparse geo-social networking data. In: ACM SIGSPATIAL’12, pp 199–208
Shimrat M (1962) Algorithm 112: position of point relative to polygon. Commun ACM 5(8):434
Hormann K, Agathos A (2001) The point in polygon problem for arbitrary polygons. Comput Geom 20(3):131–144
Kupper A, Bareth U, Freese B (2011) Geofencing and background tracking—the next features in LBS. In: INFORMATIK11
Yu Y, Tang SH, Zimmermann R (2013) Edge-based locality sensitive hashing for efficient geo-fencing application. In: ACM SIGSPATIAL’13, pp 576–579
Qu Y, Zhang J (2013) Trade area analysis using user generated mobile location data. In: WWW’13, pp 1053–1064
Quercia D, Di Lorenzo G, Calabrese F, Ratti C (2011) Mobile phones and outdoor advertising: measurable advertising. IEEE Pervasive Comput 10(2):28–36
Scellato S, Noulas A, Lambiotte R, Mascolo C (2011) Socio-spatial properties of online location-based social networks. In: ICWSM’11
Scellato S, Mascolo C, Musolesi M, Crowcroft J (2011) Track globally, deliver locally: improving content delivery networks by tracking geographic social cascades. In: WWW’11, pp 457–466
Leung D, Newsam S (2012) Exploring geotagged images for land-use classification. In: GeoMM’12, pp 3–8
Hauger D, Schedl M (2012) Exploring geospatial music listening patterns in microblog data. In: 10th international workshop on adaptive multimedia retrieval
Ikawa Y, Vukovic M, Rogstadius J, Murakami A (2013) Location-based insights from the social web. In: WWW’13 companion, pp 1013–1016
Eisenstein J, Ahmed A, Xing E (2011) Sparse additive generative models of text. In: ICML’11, pp 1041–1048
Hong L, Ahmed A, Gurumurthy S, Smola A, Tsioutsiouliklis K (2012) Discovering geographical topics in the Twitter stream. In: WWW’12, pp 769–778
Joachims T, Finley T, Yu CN (2009) Cutting-plane training of structural SVMs. Mach Learn 77(1):27–59
Hofmann T (1999) Probabilistic latent semantic indexing. In: ACM SIGIR’99, pp 50–57
Kamahara J, Nagamatsu T, Tanaka N (2012) Conjunctive ranking function using geographic distance and image distance for geotagged image retrieval. In: GeoMM’12, pp 9–14
Liu Y, Shi Z, Wang G, Guan H (2012) Find you wherever you are: geographic location and environment context-based pedestrian detection. In: GeoMM’12, pp 27–32
Robertson S (2004) Understanding inverse document frequency: on theoretical arguments for IDF. J Doc 60(5):503–520
Zheng Y, Zhang L, Xie X, Ma WY (2009) Mining interesting locations and travel sequences from GPS trajectories. In: WWW’09, pp 791–800
Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022
Kamath KY, Caverlee J, Lee K, Cheng Z (2013) Spatio-temporal dynamics of online memes: a study of geo-tagged tweets. In: WWW’13, pp 667–678
Yamasaki T, Gallagher A, Chen T (2013) Personalized intra- and inter-city travel recommendation using large-scale geotags. In: GeoMM’13, pp 25–30
Yu Y, Aizawa K, Yamasaki T, Zimmermann R (2014) Emerging topics on personalized and localized multimedia information systems. In: ACM MM’14
Wang J (1999) A survey of web caching schemes for the Internet. ACM SIGCOMM Comput Commun Rev 29(5):36–46
Acknowledgments
The work presented was in part supported by the Singapore National Research Foundation under its International Research Centre @ Singapore Funding Initiative and administered by the IDM Programme Office.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Yu, Y., Zimmermann, R., Tang, S. (2015). Social Interactions over Location-Aware Multimedia Systems. In: Baughman, A., Gao, J., Pan, JY., Petrushin, V. (eds) Multimedia Data Mining and Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-14998-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-14998-1_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14997-4
Online ISBN: 978-3-319-14998-1
eBook Packages: Computer ScienceComputer Science (R0)