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  1. Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN '12)
  2. SNAIR: a framework for personalised recommendations based on social network analysis
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The anatomy of Sindbad: a location-aware social networking system
Traffic observatory: a system to detect and locate traffic events and conditions using Twitter
TweoLocator: a non-intrusive geographical locator system for Twitter
Parallelization of ensemble neural networks for spatial land-use modeling
Can off-the-shelf object detectors be used to extract geographic information from geo-referenced social multimedia?
Multimodal geo-tagging in social media websites using hierarchical spatial segmentation
SNAIR: a framework for personalised recommendations based on social network analysis
Exploratory analysis on heterogeneous tag-point patterns for ranking and extracting hot-spot related tags
Public checkins versus private queries: measuring and evaluating spatial preference

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SNAIR: a framework for personalised recommendations based on social network analysis

Content Provider ACM Digital Library
Author Gupta, Ankur Charak, Abhishek Shridhar, Saajan Shridhar, Swapan Lakhanpuria, Mithleshwar
Abstract This paper presents a social network mining and analysis framework delivering personalized recommendations to the user in a privacy-preserving manner. Recommendations are based on the core elements of social media namely location, interests, work domain, gender, friends and nature of interactions. These elements are mined from the multiple social networking applications utilized by the user. The user controls the source and nature of recommendations received through configurable privacy filters.
Starting Page 55
Ending Page 61
Page Count 7
File Format PDF
ISBN 9781450316989
DOI 10.1145/2442796.2442809
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-11-06
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Personal recommendation profile Social network analysis Social media Recommendation systems Social networks
Content Type Text
Resource Type Article
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