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Social networks have been prevalent on the Internet and become a hot research topic attracting many professionals from a variety of fields. The advances in location-acquisition and mobile communication technologies empower people to use location data with existing online social networks. The dimension of location helps bridge the gap between the physical world and online social networking services. Furthermore, people in an existing social network can expand their social structure with the new interdependency derived from their locations. As location is one of the most important components of user context, extensive knowledge about an individual’s interests, behaviors, and relationships with others can be learned from her locations. These kinds of location-embedded and location-driven social structures are known as location-based social networks. The objective of this workshop is to provide professionals, researchers, and technologists with a single forum where they can discuss and share the state-of-the-art of LBSN development and applications, present their ideas and contributions, and set future directions in emerging innovative research for location based social networks.

征稿信息

重要日期

2016-09-15
初稿截稿日期

征稿范围

Topics of interest include, but not limited to, the following aspects :

Understanding users in LBSNs

  • User preference modeling

  • User mobility modeling and analysis

  • Real-world user activity sensing and recognition

  • User similarity computing based on locations

  • Link prediction and social tiers inference

  • Friend recommendations and community discovery

  • Expert discovery and influential person identification

  • User intension understanding

Understanding locations in LBSNs

  • Hot spots, significant places, and interesting locations detection

  • Generic or personalized location recommendations

  • Popular travel routes discovery from social media

  • Trip planning and itinerary suggestion for users

  • Location annotation and semantic meaning identification

  • Location prediction and location privacy

  • Anomaly detection and event discovery from social media

  • Trajectory data mining in LBSNs

Information sharing and Data management in LBSNs

  • Location and location-related data sharing

  • Location and location-tagged media visualization

  • Human-computer interaction in LBSNs

  • Information retrieval in LBSNs

  • Data management in LBSNs

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重要日期
  • 10月31日

    2016

    会议日期

  • 09月15日 2016

    初稿截稿日期

  • 10月31日 2016

    注册截止日期

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