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  Chua, Tat Add to Alert Profile  
 
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  1 - 5 of 6 reviews    
  Neural graph collaborative filtering
Wang X., He X., Wang M., Feng F., Chua T.  SIGIR 2019 (Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France, Jul 21-25, 2019) 165-174, 2019.  Type: Proceedings

Typically, collaborative filtering (CF) is simply a nearest neighbor (NN) algorithm used either in its original form or in machine learning (ML), especially in supervised learning, to predict user preferences in recommender systems. He...
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Oct 14 2020  
  Mining user generated content
Moens M., Li J., Chua T., Chapman & Hall/CRC, Boca Raton, FL, 2014. 474 pp.  Type: Book (978-1-466557-40-6)

Managing users in system life cycles has remained a challenging area in computing environments. We often come across various methods and tools like user-centered design (UCD), service-oriented architecture (SOA), and user interfaces th...
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Jun 1 2015  
  Personalized recommendations of locally interesting venues to tourists via cross-region community matching
Zhao Y., Nie L., Wang X., Chua T. ACM Transactions on Intelligent Systems and Technology 5(3): 1-26, 2014.  Type: Article

A challenging problem is presented in this paper: recommending interesting places to tourists. The authors address the different challenges to provide recommendations that can be characterized by novelty and high relevance. To achieve ...
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Sep 19 2014  
  GPSView: a scenic driving route planner
Zheng Y., Yan S., Zha Z., Li Y., Zhou X., Chua T., Jain R. ACM Transactions on Multimedia Computing, Communications, and Applications 9(1): 1-18, 2013.  Type: Article

Early work on the development of GPSView, an augmented global positioning system (GPS) that returns an optimal scenic driving route, is presented. This is in contrast to commonly used systems for automobiles that provide the shortest r...
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Jun 25 2013  
  Learning Object Models from Semistructured Web Documents
Ye S., Chua T. IEEE Transactions on Knowledge and Data Engineering 18(3): 334-349, 2006.  Type: Article

Web agents need to sift through an unwieldy amount of human-oriented data on the Web, which is not an easy task. Ye and Chua report on a method to infer object models and extract data from semistructured, tabulated Web pages. Their app...
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Mar 22 2006  

 
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