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Volumn , Issue , 2018, Pages 1-5

A comparative analysis of text similarity measures and algorithms in research paper recommender systems

Author keywords

big data; data mining; documents; information retrieval; recommender systems; similarity metrics and measures

Indexed keywords

BIG DATA; DECISION TREES; INFORMATION RETRIEVAL; LEARNING ALGORITHMS; LEARNING SYSTEMS; RECOMMENDER SYSTEMS; REGRESSION ANALYSIS; SEARCH ENGINES; TEXT PROCESSING;

EID: 85048989162     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICTAS.2018.8368766     Document Type: Conference Paper
Times cited : (40)

References (11)
  • 2
    • 84929952432 scopus 로고    scopus 로고
    • A comprehensive evaluation of scholarly paper recommendation using potential citation papers
    • K. Sugiyama and M.-Y. Kan, "A comprehensive evaluation of scholarly paper recommendation using potential citation papers, " International Journal on Digital Libraries, vol. 16, pp. 91-109, 2015.
    • (2015) International Journal on Digital Libraries , vol.16 , pp. 91-109
    • Sugiyama, K.1    Kan, M.-Y.2
  • 11
    • 84944790255 scopus 로고    scopus 로고
    • A comparison of offline evaluations, online evaluations, and user studies in the context of research-paper recommender systems
    • J. Beel and S. Langer, "A comparison of offline evaluations, online evaluations, and user studies in the context of research-paper recommender systems, " in International Conference on Theory and Practice of Digital Libraries, 2015, pp. 153-168.
    • (2015) International Conference on Theory and Practice of Digital Libraries , pp. 153-168
    • Beel, J.1    Langer, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.