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Subject: Recommender Systems Subject: Collaborative Filtering Departments: Department of Electrical and Computer Engineering

  • Online User Purchasing Behavior Modeling

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    Fall 2017

    Gong, Xiaohui

    With the proliferation of e-commerce business, the study of online user purchasing behavior plays an important role in improving purchasing experiences of users as well as providing valuable intelligence to sellers. While most previous research efforts focused on explicit user behavior modeling,...

  • Utilizing Context for Novel Point of Interest Recommendation

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    Fall 2017

    Morawski, Jason M

    Recommender systems are a modern solution for suggesting new items to users. One of their uses is for novel point of interest recommendation, recommending locations to a user which they have not visited. This can be applied to a location-based social network, which contains information about...

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