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  • Query-Driven Sampling for Collective Entity Resolution

    May 21, 2015     Comment Closed     publications, research directions

    Christan Grant One of the research theme of the UF Data Science Research lab is to adapt machine learning algorithm to real-time interactive query engines. Our prior work looked at implementing and optimizing information extraction and statistical machine learning operations in exploratory query processing systems. To push the envelop further, our newly completed paper (under-submission)

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Recent Posts

  • DBSim: Extensible Database Simulator for Fast Prototyping In-Database Algorithms
  • DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queries
  • A Brief Overview of Weak Supervision
  • DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
  • IDTrees Data Science Challenge: 2017