Skip to main content

2017 | OriginalPaper | Buchkapitel

Personalized POI Groups Recommendation in Location-Based Social Networks

verfasst von : Fei Yu, Zhijun Li, Shouxu Jiang, Xiaofei Yang

Erschienen in: Web and Big Data

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

With development of urban modernization, there are a large number of hop spots covering the entire city, defined as Pionts-of-Interest (POIs) Group consist of POIs. POI Groups have a significant impact on people’s lives and urban planning. Every person has her/his own personalized POI Groups (PPGs) based on preferences and friendship in location-based social networks (LBSNs). However, there are almost no researches on this aspect in recommendation systems. This paper proposes a novel PPGs Recommendation algorithm, and models the PPGs by expanding the model of DBSCAN. Our model considers the degree to each PPG covering the target users’ POI preferences. The system recommends the target user with the PPGs which have the top-N largest scores, and it is one NP-hard problem. This paper proposes the greedy algorithm to solve it. Extensive experiments on the two LBSN datasets illustrate the effectiveness of our proposed algorithm.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

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!

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!

Literatur
1.
Zurück zum Zitat Yu, F., Che, N., Li, Z., Li, K., Jiang, S.: Friend recommendation considering preference coverage in location-based social networks. In: Kim, J., Shim, K., Cao, L., Lee, J.-G., Lin, X., Moon, Y.-S. (eds.) PAKDD 2017. LNCS, vol. 10235, pp. 91–105. Springer, Cham (2017). doi:10.1007/978-3-319-57529-2_8 CrossRef Yu, F., Che, N., Li, Z., Li, K., Jiang, S.: Friend recommendation considering preference coverage in location-based social networks. In: Kim, J., Shim, K., Cao, L., Lee, J.-G., Lin, X., Moon, Y.-S. (eds.) PAKDD 2017. LNCS, vol. 10235, pp. 91–105. Springer, Cham (2017). doi:10.​1007/​978-3-319-57529-2_​8 CrossRef
2.
Zurück zum Zitat Ester, M., Kriegel, H.P., Sander, J., et al.: A density-based algorithm for discovering clusters in large spatial databases with noise. Kdd 96(34), 226–231 (1996) Ester, M., Kriegel, H.P., Sander, J., et al.: A density-based algorithm for discovering clusters in large spatial databases with noise. Kdd 96(34), 226–231 (1996)
3.
Zurück zum Zitat Shi, J., Mamoulis, N., Wu, D., et al.: Density-based place clustering in geo-social networks. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, pp. 99–110. ACM (2014) Shi, J., Mamoulis, N., Wu, D., et al.: Density-based place clustering in geo-social networks. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, pp. 99–110. ACM (2014)
4.
Zurück zum Zitat Li, J.P., Xu, Y., Zhao, L.: OPGs-Rec: organized-POI-groups based recommendation. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds.) APWeb 2016. LNCS, vol. 9932, pp. 521–524. Springer, Cham (2016). doi:10.1007/978-3-319-45817-5_56 CrossRef Li, J.P., Xu, Y., Zhao, L.: OPGs-Rec: organized-POI-groups based recommendation. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds.) APWeb 2016. LNCS, vol. 9932, pp. 521–524. Springer, Cham (2016). doi:10.​1007/​978-3-319-45817-5_​56 CrossRef
5.
Zurück zum Zitat Li, Y., Wu, D., Xu, J., et al.: Spatial-aware interest group queries in location-based social networks. In: ACM International Conference on Information and Knowledge Management, pp. 2643–2646. ACM (2012) Li, Y., Wu, D., Xu, J., et al.: Spatial-aware interest group queries in location-based social networks. In: ACM International Conference on Information and Knowledge Management, pp. 2643–2646. ACM (2012)
6.
Zurück zum Zitat Wang, X., Donaldson, R., Nell, C., et al.: Recommending groups to users using user-group engagement and time-dependent matrix factorization. In: Thirtieth AAAI Conference on Artificial Intelligence, pp. 1331–1337. AAAI Press (2016) Wang, X., Donaldson, R., Nell, C., et al.: Recommending groups to users using user-group engagement and time-dependent matrix factorization. In: Thirtieth AAAI Conference on Artificial Intelligence, pp. 1331–1337. AAAI Press (2016)
7.
Zurück zum Zitat Ye, M., Yin, P., Lee, W.C., et al.: Exploiting geographical influence for collaborative point-of-interest recommendation. In: Proceeding of the International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011, Beijing, July 2011, pp. 325–334 (2011) Ye, M., Yin, P., Lee, W.C., et al.: Exploiting geographical influence for collaborative point-of-interest recommendation. In: Proceeding of the International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2011, Beijing, July 2011, pp. 325–334 (2011)
8.
Zurück zum Zitat Cheng, C., Yang, H., King, I., et al.: Fused matrix factorization with geographical and social influence in location-based social networks. Aaai 12, 17–23 (2012) Cheng, C., Yang, H., King, I., et al.: Fused matrix factorization with geographical and social influence in location-based social networks. Aaai 12, 17–23 (2012)
Metadaten
Titel
Personalized POI Groups Recommendation in Location-Based Social Networks
verfasst von
Fei Yu
Zhijun Li
Shouxu Jiang
Xiaofei Yang
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-63564-4_9