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Volumn 1691, Issue , 2016, Pages 70-72

UniMiB: Entity linking in tweets using Jaro-Winkler distance, popularity and coherence

Author keywords

Knowledge base; Named entity linking; Named entity recognition

Indexed keywords

KNOWLEDGE BASED SYSTEMS;

EID: 84992391278     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (6)
  • 2
    • 0028950887 scopus 로고
    • Probabilistic linkage of large public health data files
    • M. A. Jaro. Probabilistic linkage of large public health data files. Statistics in medicine, 14(5-7):491-498, 1995.
    • (1995) Statistics in Medicine , vol.14 , Issue.5-7 , pp. 491-498
    • Jaro, M.A.1
  • 5
    • 84992435567 scopus 로고    scopus 로고
    • Making sense of microposts (#microposts2016) named entity recognition and linking (neel) challenge
    • D. Preoţiuc-Pietro, D. Radovanović, A. E. Cano-Basave, K. Weller, and A.-S. Dadzie, editors
    • G. Rizzo, M. van Erp, J. Plu, and R. Troncy. Making Sense of Microposts (#Microposts2016) Named Entity rEcognition and Linking (NEEL) Challenge. In D. Preoţiuc-Pietro, D. Radovanović, A. E. Cano-Basave, K. Weller, and A.-S. Dadzie, editors, 6th Workshop on Making Sense of Microposts (#Microposts2016), pages 50-59, 2016.
    • (2016) 6th Workshop on Making Sense of Microposts (#Microposts2016) , pp. 50-59
    • Rizzo, G.1    Van Erp, M.2    Plu, J.3    Troncy, R.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.