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Volumn , Issue , 2013, Pages 471-474

Short text classification using wikipedia concept based document representation

Author keywords

Document Representation; Short Text Classification; Wikipedia

Indexed keywords

CONCEPT-BASED; DOCUMENT REPRESENTATION; EXPERIMENTAL EVALUATION; SHORT TEXT CLASSIFICATIONS; SHORT TEXTS; TEXT CATEGORIZATION; TEXT DATA; WIKIPEDIA;

EID: 84893773064     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITA.2013.114     Document Type: Conference Paper
Times cited : (24)

References (14)
  • 8
    • 57349117605 scopus 로고    scopus 로고
    • Learning to classify short and sparse text &web with hidden topics from large-scale data collections
    • Beijing, China
    • X.-H. Phan, et al., "Learning to classify short and sparse text &web with hidden topics from large-scale data collections," presented at the Proceedings of the 17th international conference on World Wide Web(WWW'2008), Beijing, China, 2008.
    • (2008) The Proceedings of the 17th International Conference on World Wide Web(WWW'2008)
    • Phan, X.-H.1
  • 12
    • 70449817161 scopus 로고    scopus 로고
    • An effective, low-cost measure of semantic relatedness obtained from Wikipedia links
    • D. Milne and I. Witten, "An effective, low-cost measure of semantic relatedness obtained from Wikipedia links," in AAAI 2008.
    • (2008) AAAI
    • Milne, D.1    Witten, I.2
  • 13
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • F. Sebastiani, "Machine learning in automated text categorization," ACM Comput. Surv., vol. 34, pp. 1-47, 2002.
    • (2002) ACM Comput. Surv , vol.34 , pp. 1-47
    • Sebastiani, F.1
  • 14
    • 79955702502 scopus 로고    scopus 로고
    • LIBSVM: A library for support vector machines
    • C.-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines," ACM Trans. Intell. Syst. Technol., vol. 2, pp. 1-27, 2011.
    • (2011) ACM Trans. Intell. Syst. Technol , vol.2 , pp. 1-27
    • Chang, C.-C.1    Lin, C.-J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.