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  • Query-Driven Sampling for Collective Entity Resolution

    cgrant 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

  • Efficient Conditional Rule Mining over Knowledge Bases
  • Taming The Data Monster To Make Better Decisions
  • Mining Rules Incrementally over Large Knowledge Bases
  • Multimodal Learning for Web Information Extraction
  • Archimedes: Efficient Query Processing over Probabilistic Knowledge Bases