Logo: University of Southern California

Events Calendar


  • Heterogeneous Attribute Embedding and Sequence Modeling for Recommendation with Implicit Feedback

    Fri, Mar 17, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Kuan Liu, USC/ISI

    Talk Title: Heterogeneous Attribute Embedding and Sequence Modeling for Recommendation with Implicit Feedback

    Series: Natural Language Seminar

    Abstract: Incorporating implicit feedback into a recommender system is a challenging problem due to sparse and noisy observations. I will present our approaches that exploit heterogeneous attributes and sequence properties within the observations. We build a neural network framework to embed heterogeneous attributes in an end-to-end fashion, and apply the framework to three sequence-based models. Our methods achieve significant improvements on four large scale datasets compared to state-of-the-art baseline models 30 to 90 percent relative increase in NDCG. Experimental results show that attribute embedding and sequence modeling both lead to improvements and, further, that our novel output attribute layer plays a crucial role. I will conclude with our exploratory studies that investigate why sequence modeling works well in recommendation systems and advocate its use for large scale recommendation tasks.





    Biography: Kuan Liu is a fifth year Ph.D. student at ISI/USC working with Prof. Prem Natarajan. Before that, He received a bachelor degree from Tsinghua University with a major in Computer Science. His research interests include machine learning, large scale optimization, deep learning, and applications to recommender systems, network analysis.

    Host: Marjan Ghazvininejad and Kevin Knight

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

    Audiences: Everyone Is Invited

    Contact: Peter Zamar

    OutlookiCal

Return to Calendar