• An Empirical Evaluation of Deep Learning Techniques for Human Activity Recognition

      Lu, Weijie (Auckland University of Technology, 2020)
      The recent advancement and development of human-activity recognition technology have led to the gradual entrance of smart home induction systems into residents' lives, stimulating the demand for associated products and ...
    • Incorporating Service Proximity Into Web Service Recommendation Via Tensors Decomposition

      Wu, Zhentao (Auckland University of Technology, 2019)
      The sparseness of Mashup-API rating matrix coupled with cold-start and scalability issues have been identified as the most critical challenges that affect most Collaborative filtering based Web APIs recommendation solution. ...
    • Matrix Factorisation Based Recommendation for Web Mashups

      Ou, Jacky (Auckland University of Technology, 2020)
      In recommender systems, the Internet has evolved over the years for recommending items such as music, movies, books and videos for users to boost the popularity or sales for a single item. One of the significant challenges ...
    • Transformation and Synthesis of Artifact-centric Business Processes

      Kunchala, Naga Jyothi (Auckland University of Technology, 2020)
      In today’s dynamic business environment, business process modeling (BPM) has become a fundamental tool in many organizations to gain operational benefits and stay competitive with their rivals. Thus, there is always an ...
    • Web APIs Recommendation Based on Topic Modelling and Clustering

      Zhang, Fangran (Auckland University of Technology, 2019)
      Nowadays, Recommender Systems are widely used in various web portals, while service discovery is still a great challenge for better integrating appropriate services into business scenarios. Gaining insight of the development ...