Hisrect: Features From Historical Visits And Recent Tweet For Co-Location Judgement
2020 IEEE 36TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2020)(2020)
摘要
This study explores the problem of co-location judgement, i.e., to decide whether two Twitter users are co-located at some point-of-interest (POI). We extract novel features, named HisRect, from users' historical visits and recent tweets: The former has impact on where a user visits in general, whereas the latter gives more hints about where a user is currently. To alleviate the issue of data scarcity, a semi-supervised learning (SSL) framework is designed to extract HisRect features. Moreover, we use an embedding neural network layer to decide co-location based on the difference between two users' HisRect features. Extensive experiments on real Twitter data suggest that our HisRect features and SSL framework are highly effective at deciding co-locations.
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关键词
Twitter,POI,co-location judgement,semi-supervised learning
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