Abstract
By leveraging the capabilities of modern GPS-equipped mobile devices providing social-networking services, the interest in developing advanced services that combine location-based services with social networking services is growing drastically. Based on geo-social networks that couple personal location information with personal social context information, such services are facilitated by geo-social queries that extract useful information combining social relationships and current locations of the users. In this paper, we tackle the problem of geo-social skyline queries, a problem that has not been addressed so far. Given a set of persons D connected in a social network SN with information about their current location, a geo-social skyline query reports for a given user U ε D and a given location P (not necessarily the location of the user) the pareto-optimal set of persons who are close to P and closely connected to U in SN. We measure the social connectivity between users using the widely adoted, but very expensive Random Walk with Restart method (RWR) to obtain the social distance between users in the social network. We propose an efficient solution by showing how the RWR-distance can be bounded efficiently and effectively in order to identify true hits and true drops early. Our experimental evaluation shows that our presented pruning techniques allow to vastly reduce the number of objects for which a more exact social distance has to be computed, by using our proposed bounds only.
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References
Amir, A., Efrat, A., Myllymaki, J., Palaniappan, L., Wampler, K.: Buddy tracking - efficient proximity detection among mobile friends. Pervasive and Mobile Computing 3(5), 489–511 (2007)
Angles, R., Prat-Pérez, A., Dominguez-Sal, D., Larriba-Pey, J.-L.: Benchmarking database systems for social network applications. In: Proc. GRADES. ACM (2013)
Armenatzoglou, N., Papadopoulos, S., Papadias, D.: A general framework for geo-social query processing. In: Proc. VLDB, pp. 913–924. VLDB Endowment (2013)
Berkhin, P.: Bookmark-coloring algorithm for personalized pagerank computing. Internet Mathematics 3(1), 41–62 (2006)
Borzsony, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proc. ICDE, pp. 421–430. IEEE (2001)
Brinkhoff, T.: A framework for generating network-based moving objects. GeoInformatica 6(2), 153–180 (2002)
Cho, E., Myers, S.A., Leskovec, J.: Friendship and mobility: user movement in location-based social networks. In: Proc. KDD, pp. 1082–1090. ACM (2011)
Deng, K., Zhou, Y., Shen, H.T.: Multi-source skyline query processing in road networks. In: Proc. ICDE, pp. 796–805. IEEE (2007)
Fujiwara, Y., Nakatsuji, M., Onizuka, M., Kitsuregawa, M.: Fast and exact top-k search for random walk with restart. In: Proc. VLDB, pp. 442–453. VLDB Endowment (2012)
Graf, F., Kriegel, H.-P., Renz, M., Schubert, M.: Memory-efficient A*-search using sparse embeddings. In: Proc. ACM GIS, pp. 462–465. ACM (2010)
Guttman, A.: R-Trees: A dynamic index structure for spatial searching. In: Proc. SIGMOD, pp. 47–57. ACM (1984)
Hjaltason, G.R., Samet, H.: Distance browsing in spatial databases. ACM Transactions on Database Systems 24(2), 265–318 (1999)
Huang, X., Jensen, C.S.: In-route skyline querying for location-based services. In: Kwon, Y.-J., Bouju, A., Claramunt, C. (eds.) W2GIS 2004. LNCS, vol. 3428, pp. 120–135. Springer, Heidelberg (2005)
Jang, S.M., Yoo, J.S.: Processing continuous skyline queries in road networks. In: Proc. CSA, pp. 353–356. IEEE (2008)
Konstas, I., Stathopoulos, V., Jose, J.M.: On social networks and collaborative recommendation. In: Proc. SIGIR, pp. 195–202. ACM (2009)
Kossmann, D., Ramsak, F., Rost, S.: Shooting stars in the sky: an online algorithm for skyline queries. In: Proc. VLDB, pp. 275–286. VLDB Endowment (2002)
Lin, X., Yuan, Y., Zhang, Q., Zhang, Y.: Selecting stars: The k most representitive skyline operator. In: Proc. ICDE, pp. 86–95. IEEE (2007)
Liu, W., Sun, W., Chen, C., Huang, Y., Jing, Y., Chen, K.: Circle of friend query in geo-social networks. In: Lee, S.-g., Peng, Z., Zhou, X., Moon, Y.-S., Unland, R., Yoo, J. (eds.) DASFAA 2012, Part II. LNCS, vol. 7239, pp. 126–137. Springer, Heidelberg (2012)
Morse, M., Patel, J.M., Jagadish, H.: Efficient skyline computation over low-cardinality domains. In: Proc. VLDB, pp. 267–278. VLDB Endowment (2007)
Papadias, D., Tao, Y., Fu, G., Seeger, B.: An optimal and progressive algorithm for skyline queries. In: Proc. SIGMOD, pp. 467–478. ACM (2003)
Pei, J., Jin, W., Ester, M., Tao, Y.: Catching the best views of skyline: A semantic approach based on decisive subspaces. In: Proc. VLDB, pp. 253–264. VLDB Endowment (2005)
Scellato, S., Mascolo, C., Musolesi, M., Latora, V.: Distance matters: geo-social metrics for online social networks. In: Proc. WOSN. USENIX (2010)
Tan, K.-L., Eng, P.-K., Ooi, B.C.: Efficient progressive skyline computation. In: Proc. VLDB, pp. 301–310. VLDB Endowment (2001)
Tong, H., Faloutsos, C., Pan, J.Y.: Fast random walk with restart and its applications. In: Proc. ICDM, pp. 613–622. IEEE (2006)
Zhang, C., Shou, L., Chen, K., Chen, G., Bei, Y.: Evaluating geo-social influence in location-based social networks. In: Proc. CIKM, pp. 1442–1451. ACM (2012)
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Emrich, T., Franzke, M., Mamoulis, N., Renz, M., Züfle, A. (2014). Geo-Social Skyline Queries. In: Bhowmick, S.S., Dyreson, C.E., Jensen, C.S., Lee, M.L., Muliantara, A., Thalheim, B. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science, vol 8422. Springer, Cham. https://doi.org/10.1007/978-3-319-05813-9_6
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DOI: https://doi.org/10.1007/978-3-319-05813-9_6
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