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Renewed interest in sports as a career option and entertainment generated natural want for recommendation system. Though the realm is not much explored, this study throws some light on Sports KB generation. The paper offers an architecture which constitutes a basis to Knowledge Base in sports domain. The proposed framework encompasses Normalized Google Distance, Concept Similarity and SemantoSim. It uses Sports Blogs, AWS SPORTS Stories etc. to curate the sports Knowledge. Contrasting the pro-posed framework to existing systems that are currently in use, it achieved an accuracy of 92.13% and a minimum FDR of 0.09.

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SportsKBGen Framework: Knowledge Base Generation for Sports as a Prospective Domain

  • 会议论文

  • 发表日期：

    2025年

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  • Anamaya Vyas,
  • Gerard Deepak

摘要

Renewed interest in sports as a career option and entertainment generated natural want for recommendation system. Though the realm is not much explored, this study throws some light on Sports KB generation. The paper offers an architecture which constitutes a basis to Knowledge Base in sports domain. The proposed framework encompasses Normalized Google Distance, Concept Similarity and SemantoSim. It uses Sports Blogs, AWS SPORTS Stories etc. to curate the sports Knowledge. Contrasting the pro-posed framework to existing systems that are currently in use, it achieved an accuracy of 92.13% and a minimum FDR of 0.09.