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Crowd-Type: A Crowdsourcing-Based Tool for Type Completion in Knowledge Bases

  • Zhaoan Dong
  • Jianhong Tu
  • Ju Fan
  • Jiaheng Lu
  • Xiaoyong Du
  • Tok Wang Ling
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11158)

Abstract

Entity type completion in Knowledge Bases (KBs) is an important and challenging problem. In our recent work, we have proposed a hybrid framework which combines the human intelligence of crowdsourcing with automatic algorithms to address the problem. In this demo, we have implemented the framework in a crowdsourcing-based system, named Crowd-Type, for fine-grained type completion in KBs. In particular, Crowd-Type firstly employs automatic algorithms to select the most representative entities and assigns them to human workers, who will verify the types for assigned entities. Then, the system infers and determines the correct types for all entities utilizing both the results of crowdsourcing and machine-based algorithms. Our system gives a vivid demonstration to show how crowdsourcing significantly improves the performance of automatic type completion algorithms.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Zhaoan Dong
    • 2
  • Jianhong Tu
    • 2
  • Ju Fan
    • 2
  • Jiaheng Lu
    • 1
    • 2
  • Xiaoyong Du
    • 2
  • Tok Wang Ling
    • 3
  1. 1.Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland
  2. 2.DEKE, MOE and School of InformationRenmin University of ChinaBeijingChina
  3. 3.School of ComputingNational University of SingaporeSingaporeSingapore

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