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Context Awareness in Mobile Systems

  • Chapter
Data Management in Pervasive Systems

Part of the book series: Data-Centric Systems and Applications ((DCSA))

Abstract

Context represents any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and application themselves. The ubiquity of mobile devices (e.g., smartphones, GPS devices) has in part motivated the use of contextual information in modern mobile applications. From one perspective, context in mobile systems can fall into three categories: (a) user context that includes the personal attributes of the user, e.g., spatial location and budget; (b) point-of-interest (POI) context, e.g., restaurant location, operating time, and rating; and (c) environmental context, e.g., weather and road conditions. Incorporating such context in applications provided to mobile users may significantly enhance the quality of service in terms of finding more related answers. This chapter first gives a brief overview of context and context awareness in mobile systems. It then discusses different ways of expressing the spatial location context within mobile services. The chapter later describes three main application examples that can take advantage of various mobile contexts, namely, social news feed, microblogging (e.g., Twitter) and recommendation services. The chapter finally presents a generic method that incorporates context and user preference awareness in database systems—which may serve as a backbone for context-aware mobile applications.

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References

  1. Abdelhaq, H., Sengstock, C., Gertz, M.: EvenTweet: online localized event detection from Twitter. In: Proceedings of the International Conference on Very Large Data Bases, VLDB (2013)

    Google Scholar 

  2. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)

    Article  Google Scholar 

  3. After Boston Explosions, People Rush to Twitter for Breaking News. http://www.latimes.com/business/technology/la-fi-tn-after-boston-explosions-people-rush-to-twitter-for-breaking-news-20130415,0,3729783.story (2013)

  4. Agrawal, R., Wimmers, E.L.: A framework for expressing and combining preferences. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (2000)

    Book  Google Scholar 

  5. Agrawal, R., Rantzau, R., Terzi, E.: Context-sensitive ranking. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (2006)

    Book  Google Scholar 

  6. Alsubaiee, S., Altowim, Y., Altwaijry, H., Behm, A., Borkar, V.R., Bu, Y., Carey, M.J., Grover, R., Heilbron, Z., Kim, Y.S., Li, C., Onose, N., Pirzadeh, P., Vernica, R., Wen, J.: ASTERIX: an open source system for “Big Data” management and analysis. Proc. Int. Conf. Very Large Data Bases 5(12), 1898–1901 (2012)

    Google Scholar 

  7. Apple buys social media analytics firm Topsy Labs. http://www.bbc.co.uk/news/business-25195534 (2013)

  8. Arvanitis, A., Koutrika, G.: Towards preference-aware relational databases. In: Proceedings of the International Conference on Data Engineering, ICDE, pp. 426–437 (2012)

    Google Scholar 

  9. Arvanitis, A., Koutrika, G.: Prefdb: supporting preferences as first-class citizens in relational databases. IEEE Trans. Knowl. Data Eng. 26(6), 1430–1446 (2014)

    Article  Google Scholar 

  10. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press/Addison-Wesley, New York (1999)

    Google Scholar 

  11. Bao, J., Mokbel, M.F., Chow, C.Y.: GeoFeed: a location-aware news feed system. In: ICDE, pp. 54–65 (2012)

    Google Scholar 

  12. Borzsonyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: ICDE, pp. 421–430 (2001)

    Google Scholar 

  13. Brown, M.G.: Supporting user mobility. In: IFIP World Conference on Mobile Communications (1996)

    Book  Google Scholar 

  14. Brown, P.J., Bovey, J.D., Chen, X.: Context-aware applications: from the laboratory to the marketplace. IEEE Pers. Commun. 4(5), 58–64 (1997)

    Article  Google Scholar 

  15. Budak, C., Georgiou, T., Agrawal, D., Abbadi, A.E.: GeoScope: online detection of geo-correlated information trends in social networks. In: Proceedings of the International Conference on Very Large Data Bases, VLDB (2014)

    Google Scholar 

  16. Busch, M., Gade, K., Larson, B., Lok, P., Luckenbill, S., Lin, J.: Earlybird: real-time search at Twitter. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE (2012)

    Google Scholar 

  17. Chan, C.Y., Jagadish, H., Tan, K.L., Tung, A.K., Zhang, Z.: Finding k-dominant skylines in high dimensional space. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (2006)

    Book  Google Scholar 

  18. Chen, C., Li, F., Ooi, B.C., Wu, S.: TI: an efficient indexing mechanism for real-time search on tweets. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (2011)

    Book  Google Scholar 

  19. Cheng, R., Xia, Y., Prabhakar, S., Shah, R.: Change tolerant indexing for constantly evolving data. In: ICDE (2005)

    Google Scholar 

  20. Chomicki, J.: Querying with intrinsic preferences. In: Proceedings of the International Conference on Extending Database Technology, EDBT (2002)

    Book  Google Scholar 

  21. Chomicki, J.: Preference formulas in relational queries. ACM Trans. Database Syst. 28(4), 427–466 (2003)

    Article  Google Scholar 

  22. Chow, C.Y., Bao, J., Mokbel, M.F.: Towards location-based social networking services. In: The 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks (2010)

    Google Scholar 

  23. Cooperstock, J.R., Tanikoshi, K., Beirne, G., Narine, T., Buxton, W.: Evolution of a reactive environment. In: Proceedings of the International Conference on Human Factors in Computing Systems, CHI (1995)

    Book  Google Scholar 

  24. Dey, A.K.: Understanding and using context. Pers. Ubiquit. Comput. 5(1), 4–7 (2001)

    Article  Google Scholar 

  25. Dey, A.K., Abowd, G.D., Wood, A.: CyberDesk: a framework for providing self-integrating context-aware services. Knowl.-Based Syst. 11(1), 3–13 (1998)

    Article  Google Scholar 

  26. Elrod, S., Hall, G., Costanza, R., Dixon, M., des Rivières, J.: Responsive office environments. Commun. ACM 36(7), 84–85 (1993)

    Google Scholar 

  27. Facebook Statistics. https://www.facebook.com/business/power-of-advertising (2012)

  28. Feng, L., Apers, P.M.G., Jonker, W.: Towards context-aware data management for ambient intelligence. In: International Conference of Database and Expert Systems (2004)

    Book  Google Scholar 

  29. Fickas, S., Kortuem, G., Segall, Z.: Software organization for dynamic and adaptable wearable systems. In: International Symposium on Wearable Computers, pp. 56–63 (1997)

    Google Scholar 

  30. Güting, R.H., de Almeida, V.T., Ansorge, D., Behr, T., Ding, Z., Höse, T., Hoffmann, F., Spiekermann, M., Telle, U.: SECONDO: an extensible DBMS platform for research prototyping and teaching. In: Proceedings of the International Conference on Data Engineering, ICDE (2005)

    Google Scholar 

  31. Harvard Tweet Map. http://worldmap.harvard.edu/tweetmap/ (2013)

  32. Hong, L., Ahmed, A., Gurumurthy, S., Smola, A.J., Tsioutsiouliklis, K.: Discovering geographical topics in the twitter stream. In: Proceedings of the International Conference on World Wide Web, WWW (2012)

    Book  Google Scholar 

  33. Hristidis, V., Koudas, N., Papakonstantinou, Y.: PREFER: a system for the efficient execution of multi-parametric ranked queries. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (2001)

    Book  Google Scholar 

  34. Hull, R., Neaves, P., Bedford-Roberts, J.: Towards situated computing. In: International Symposium on Wearable Computers (1997)

    Book  Google Scholar 

  35. Jeung, H., Yiu, M.L., Zhou, X., Jensen, C.S.: Path prediction and predictive range querying in road network databases. VLDB J. 19(4), 585–602 (2010)

    Article  Google Scholar 

  36. Jin, W., Morse, M., Patel, J., Ester, M., Hu, Z.: Evaluating skylines in the presence of equi-joins. In: Proceedings of the International Conference on Data Engineering, ICDE, pp. 249–260 (2010)

    Google Scholar 

  37. Khalefa, M.E., Mokbel, M.F., Levandoski, J.J.: Prefjoin: an efficient preference-aware join operator. In: Proceedings of the International Conference on Data Engineering, ICDE, pp. 995–1006 (2011)

    Google Scholar 

  38. KieĂźling, W.: Foundations of preferences in database systems. In: Proceedings of the International Conference on Very Large Data Bases, VLDB (2002)

    Book  Google Scholar 

  39. Kießling, W., Köstler, G.: Preference SQL: design, implementation, experiences. In: Proceedings of the International Conference on Very Large Data Bases, VLDB (2002)

    Google Scholar 

  40. Kießling, W., Endres, M., Wenzel, F.: The preference sql system - an overview. IEEE Data Eng. Bull. 34(2), 11–18 (2011)

    Google Scholar 

  41. Koutrika, G., Ioannidis, Y.: Personalization of queries in database systems. In: Proceedings of the International Conference on Data Engineering, ICDE (2004)

    Book  Google Scholar 

  42. Koutrika, G., Ioannidis, Y.: Constrained optimalities in query personalization. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (2005)

    Book  Google Scholar 

  43. Koutrika, G., Ioannidis, Y.E.: Personalized queries under a generalized preference model. In: Proceedings of the International Conference on Data Engineering, ICDE (2005)

    Book  Google Scholar 

  44. Lacroix, M., Lavency, P.: Preferences: putting more knowledge into queries. In: Proceedings of the International Conference on Very Large Data Bases, VLDB (1987)

    Google Scholar 

  45. Levandoski, J.J., Khalefa, M., Mokbel, M.F.: FlexPref: a framework for extensible preference evaluation in database systems. In: Proceedings of the International Conference on Data Engineering, ICDE, pp. 828–839 (2010)

    Google Scholar 

  46. Levandoski, J., Sarwat, M., Eldawy, A., Mokbel, M.: LARS: a location-aware recommender system. In: ICDE, pp. 450–461 (2012)

    Google Scholar 

  47. Levandoski, J.J., Sarwat, M., Mokbel, M.F., Ekstrand, M.D.: RecStore: an extensible and adaptive framework for online recommender queries inside the database engine. In: Proceedings of the International Conference on Extending Database Technology, EDBT (2012)

    Book  Google Scholar 

  48. Li, R., Lei, K.H., Khadiwala, R., Chang, K.C.C.: TEDAS: a Twitter-based event detection and analysis system. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE (2012)

    Google Scholar 

  49. Linden, G., et al.: Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Comput. 7(1), 76–80 (2003)

    Google Scholar 

  50. Liu, W., Zheng, Y., Chawla, S., Yuan, J., Xing, X.: Discovering spatio-temporal causal interactions in traffic data streams. In: Proceedings of the ACM International Conference on Knowledge and Data Discovery, KDD (2011)

    Book  Google Scholar 

  51. Magdy, A., Alarabi, L., Al-Harthi, S., Musleh, M., Ghanem, T., Ghani, S., Mokbel, M.: Taghreed: a system for querying, analyzing, and visualizing geotagged microblogs. In: Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS (2014)

    Book  Google Scholar 

  52. Magdy, A., Aly, A.M., Mokbel, M.F., Elnikety, S., He, Y., Nath, S.: Mars: real-time spatio-temporal queries on microblogs. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE, pp. 1238–1241 (2014)

    Google Scholar 

  53. Magdy, A., Mokbel, M.F., Elnikety, S., Nath, S., He, Y.: Mercury: a memory-constrained spatio-temporal real-time search on microblogs. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE, pp. 172–183 (2014)

    Google Scholar 

  54. Marcus, A., Bernstein, M.S., Badar, O., Karger, D.R., Madden, S., Miller, R.C.: Twitinfo: aggregating and visualizing microblogs for event exploration. In: Proceedings of the International Conference on Human Factors in Computing Systems, CHI (2011)

    Book  Google Scholar 

  55. Mokbel, M.F., Aref, W.G.: PLACE: a scalable location-aware database server for spatio-temporal data streams. IEEE Data Eng. Bull. 28(3), 3–10 (2005)

    Google Scholar 

  56. Mokbel, M.F., Xiong, X., Aref, W.G.: SINA: scalable incremental processing of continuous queries in spatio-temporal databases. In: SIGMOD (2004)

    Book  Google Scholar 

  57. Mokbel, M.F., Xiong, X., Aref, W.G., Hambrusch, S., Prabhakar, S., Hammad, M.: PLACE: a query processor for handling real-time spatio-temporal data streams (Demo). In: Proceedings of the International Conference on Very Large Data Bases, VLDB (2004)

    Book  Google Scholar 

  58. New Features on Twitter for Windows Phone 3.0. https://blog.twitter.com/2013/new-features-on-twitter-for-windows-phone-30 (2013)

  59. Phelan, O., McCarthy, K., Smyth, B.: Using twitter to recommend real-time topical news. In: Proceedings of the ACM Conference on Recommender Systems, RecSys (2009)

    Book  Google Scholar 

  60. Prabhakar, S., Xia, Y., Kalashnikov, D.V., Aref, W.G., Hambrusch, S.E.: Query indexing and velocity constrained indexing: scalable techniques for continuous queries on moving objects. IEEE Trans. Comput. 51(10), 1124–1140 (2002)

    Article  MathSciNet  Google Scholar 

  61. Raghavan, V., Rundensteiner, E.: Progressive result generation for multi-criteria decision support queries. In: Proceedings of the International Conference on Data Engineering, ICDE, pp. 733–744 (2010)

    Google Scholar 

  62. Rashid, A.M., Albert, I., Coslely, D., Lam, S.K., McNee, S.M., Konstan, J.A., Riedl, J.: Getting to know you: learning new user preferences in recommender systems. In: Proceedings of the International Conference on Intelligent User Interfaces (2002)

    Book  Google Scholar 

  63. Rekimoto, J., Ayatsuka, Y., Hayashi, K.: Augment-able reality: situated communication through physical and digital spaces. In: International Symposium on Wearable Computers (1998)

    Google Scholar 

  64. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: CSWC (1994)

    Book  Google Scholar 

  65. Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes twitter users: real-time event detection by social sensors. In: Proceedings of the International Conference on World Wide Web, WWW (2010)

    Book  Google Scholar 

  66. Sankaranarayanan, J., Samet, H., Teitler, B.E., Lieberman, M.D., Sperling, J.: TwitterStand: news in tweets. In: Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS (2009)

    Book  Google Scholar 

  67. Sarwat, M., Bao, J., Eldawy, A., Levandoski, J.J., Magdy, A., Mokbel, M.F.: Sindbad: a location-based social networking system. In: SIGMOD, pp. 649–652 (2012)

    Google Scholar 

  68. Sarwat, M., Avery, J., Mokbel, M.F.: RecDB in action: recommendation made easy in relational databases. PVLDB 6(12), 1242–1245 (2013)

    Google Scholar 

  69. Sarwat, M., Levandoski, J.J., Eldawy, A., Mokbel, M.F.: LARS*: an efficient and scalable location-aware recommender system. IEEE Trans. Knowl. Data Eng. 26(6), 1384–1399 (2014)

    Article  Google Scholar 

  70. Schilit, B.N., Adams, N.I., Want, R.: Context-aware computing applications. In: Workshop on Mobile Computing Systems and Applications (1994)

    Book  Google Scholar 

  71. Silberstein, A., Terrace, J., Cooper, B.F., Ramakrishnan, R.: Feeding frenzy: selectively materializing user’s event feed. In: Proceedings of the ACM International Conference on Management of Data, SIGMOD, pp. 831–842 (2010)

    Google Scholar 

  72. Sina Weibo, China’s Twitter, comes to rescue amid flooding in Beijing. http://thenextweb.com/asia/2012/07/23/sina-weibo-chinas-twitter-comes-to-rescue-amid-flooding-in-beijing/ (2012)

  73. Singh, V.K., Gao, M., Jain, R.: Situation detection and control using spatio-temporal analysis of microblogs. In: Proceedings of the International Conference on World Wide Web, WWW (2010)

    Book  Google Scholar 

  74. Skovsgaard, A., Sidlauskas, D., Jensen, C.S.: Scalable top-k spatio-temporal term querying. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE, pp. 148–159 (2014)

    Google Scholar 

  75. Stefanidis, K., Pitoura, E.: Fast contextual preference scoring of database tuples. In: Proceedings of the International Conference on Extending Database Technology, EDBT (2008)

    Book  Google Scholar 

  76. Stefanidis, K., Pitoura, E., Vassiliadis, P.: Adding context to preferences. In: Proceedings of the International Conference on Data Engineering, ICDE (2007)

    Book  Google Scholar 

  77. Topsy Pro Analytics: Find the insights that matter. http://topsy.com/ (2013)

  78. TweetTracker: track, analyze, and understand activity on Twitter. http://tweettracker.fulton.asu.edu/ (2013)

  79. Twitter Data Grants.. https://blog.twitter.com/2014/introducing-twitter-data-grants (2014)

  80. Twitter Statistics. http://expandedramblings.com/index.php/march-2013-by-the-numbers-a-few-amazing-twitter-stats/ (2013)

  81. van Bunningen, A.H., Feng, L., Apers, P.M.G.: A context-aware preference model for database querying in an ambient intelligent environment. In: International Conference of Database and Expert Systems (2006)

    Book  Google Scholar 

  82. Watanabe, K., Ochi, M., Okabe, M., Onai, R.: Jasmine: A real-time local-event detection system based on geolocation information propagated to microblogs. In: Proceedings of the ACM International Conference on Information and Knowledge Management, CIKM (2011)

    Book  Google Scholar 

  83. Wenzel, F., Endres, M., Mandl, S., Kießling, W.: Complex preference queries supporting spatial applications for user groups. Proc VLDB Endowment 5(12), 1946–1949 (2012)

    Article  Google Scholar 

  84. Wolfson, O., Sistla, A.P., Xu, B., Zhou, J., Chamberlain, S.: DOMINO: databases for MovINg objects tracking (Demo). In: Proceedings of the ACM International Conference on Management of Data, SIGMOD (1999)

    Book  Google Scholar 

  85. Wu, L., Lin, W., Xiao, X., Xu, Y.: LSII: an indexing structure for exact real-time search on microblogs. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE (2013)

    Google Scholar 

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

    Book  Google Scholar 

  87. Yao, J., Cui, B., Xue, Z., Liu, Q.: Provenance-based indexing support in micro-blog platforms. In: Proceedings of the IEEE International Conference on Data Engineering, ICDE (2012)

    Book  Google Scholar 

  88. Yiu, M.L., Mamoulis, N.: Efficient processing of top-k dominating queries on multi-dimensional data. In: VLDB, pp. 483–494 (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Arizona State University, Tempe, AZ, USA

    Mohamed Sarwat

  2. Microsoft Research Asia, Beijing, China

    Jie Bao

  3. City University of Hong Kong, Hong Kong, China

    Chi-Yin Chow

  4. Microsoft Research, Redmond, WA, USA

    Justin Levandoski

  5. University of Minnesota, Minneapolis, MN, USA

    Amr Magdy & Mohamed F. Mokbel

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  1. Mohamed Sarwat
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  2. Jie Bao
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  3. Chi-Yin Chow
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  4. Justin Levandoski
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  5. Amr Magdy
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  6. Mohamed F. Mokbel
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Correspondence to Mohamed Sarwat .

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Editors and Affiliations

  1. UniversitĂ  di Salerno, Salerno, Italy

    Francesco Colace

  2. UniversitĂ  di Salerno, Salerno, Italy

    Massimo De Santo

  3. UniversitĂ  di Napoli, Napoli, Italy

    Vincenzo Moscato

  4. UniversitĂ  di Napoli, Napoli, Italy

    Antonio Picariello

  5. Politecnico di Milano, Milano, Italy

    Fabio A. Schreiber

  6. Politecnico di Milano, Milano, Italy

    Letizia Tanca

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Sarwat, M., Bao, J., Chow, CY., Levandoski, J., Magdy, A., Mokbel, M.F. (2015). Context Awareness in Mobile Systems. In: Colace, F., De Santo, M., Moscato, V., Picariello, A., Schreiber, F., Tanca, L. (eds) Data Management in Pervasive Systems. Data-Centric Systems and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-20062-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-20062-0_13

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