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	Liu, Kai     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending Date Reviewed     1 - 3 of 3 reviews       Deep item-based collaborative filtering for top-N recommendation Xue F., He X., Wang X., Xu J., Liu K., Hong R. ACM Transactions on Information Systems 37(3): 1-25, 2019.  Type: Article Recommender systems are an essential component in digital platforms, nudging consumers toward more efficient decision making by predicting and presenting products and services in a personalized ranking order that is of top interest. By...... Nov 19 2019     A two-stage framework for 3D face reconstruction from RGBD images Wang K., Wang X., Pan Z., Liu K. IEEE Transactions on Pattern Analysis and Machine Intelligence 36(8): 1493-1504, 2014.  Type: Article The application of MS Kinect is popular since it provides the user with color images with depth in real time. Related research in computer graphics has been focused on getting structured information out of the raw data. Although this i...... Apr 8 2015     Data scheduling for multi-item requests in multi-channel on-demand broadcast environments Liu K., Lee V., Leung K.  MobiDE 2008 (Proceedings of the 7th ACM International Workshop on Data Engineering for Wireless and Mobile Access, Vancouver, Canada, Jun 13, 2008) 47-54, 2008.  Type: Proceedings Liu, Lee, and Leung introduce a new algorithm, called dynamic urgency and productivity (DUP), to overcome two problems they identify as key obstacles to optimizing data scheduling for active jobs: the request starvation and broadcast m...... Mar 29 2010
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