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Volumn , Issue , 2013, Pages 885-890

Mining causal topics in text data: Iterative topic modeling with time series feedback

Author keywords

Causal topic mining; Iterative topic mining; Time series

Indexed keywords

CAUSAL ANALYSIS; PRIOR DISTRIBUTION; PROBABILISTIC TOPIC MODELS; STOCK PRICE; TEXT MINING; TIME-SERIES DATA; TOPIC MININGS; TOPIC MODELING;

EID: 84889604012     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2505515.2505612     Document Type: Conference Paper
Times cited : (31)

References (19)
  • 5
    • 80055063924 scopus 로고    scopus 로고
    • Twitter mood predicts the stock market
    • abs/1010.3003
    • J. Bollen, H. Mao, and X.-J. Zeng. Twitter mood predicts the stock market. CoRR, abs/1010.3003, 2010.
    • (2010) CoRR
    • Bollen, J.1    Mao, H.2    Zeng, X.-J.3
  • 18
    • 33749565782 scopus 로고    scopus 로고
    • Topics over time: A non-Markov continuous-time model of topical trends
    • New York, NY, USA ACM
    • X. Wang and A. McCallum. Topics over time: a non-markov continuous-time model of topical trends. In Proceedings of the 12th ACM SIGKDD international conference, pages 424-433, New York, NY, USA, 2006. ACM.
    • (2006) Proceedings of the 12th ACM SIGKDD International Conference , pp. 424-433
    • Wang, X.1    McCallum, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.