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Volumn 5, Issue 6, 2000, Pages

INFOMINE: Promising directions in virtual library development

Author keywords

[No Author keywords available]

Indexed keywords


EID: 0742265925     PISSN: 13960466     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (22)

References (23)
  • 1
    • 0038589165 scopus 로고    scopus 로고
    • The Anatomy of a Large-Scale Hypertextual Web Search Engine
    • Sergey Brin and Lawrence Page, 1998. "The Anatomy of a Large-Scale Hypertextual Web Search Engine," Computer Networks, volume 30, numbers 1-7, pp. 107-117,
    • (1998) Computer Networks , vol.30 , Issue.1-7 , pp. 107-117
    • Brin, S.1    Page, L.2
  • 5
    • 84889122548 scopus 로고    scopus 로고
    • Creating Customized Authority Lists
    • in press. Submitted
    • Huan Chang, David Cohn, and Andrew McCallum, in press. "Creating Customized Authority Lists." Submitted to Digital Libraries 2000, and at http://citeseer.nj.nec.com/pdf/266113
    • Digital Libraries 2000
    • Chang, H.1    Cohn, D.2    McCallum, A.3
  • 7
    • 2942637070 scopus 로고    scopus 로고
    • Learning to Extract Relations from Medline
    • M. Craven, 1999. "Learning to Extract Relations from Medline," AAAI-99 Workshop, at http://www.isi.edu/∼muslea/RISE/ML4IE/ml4ie.craven.ps
    • (1999) AAAI-99 Workshop
    • Craven, M.1
  • 11
    • 52849108692 scopus 로고    scopus 로고
    • Examining Machine Learning for Adaptable End-to-End Information Extraction Systems
    • (July 19), Orlando, Fla.
    • Oren Glickman and Rosie Jones, 1999. "Examining Machine Learning for Adaptable End-to-End Information Extraction Systems," AAAI-99 Workshop on Machine Learning for Information Extraction (July 19), Orlando, Fla., and at www.isi.edu/∼muslea/RISE/ML4IE/ml4ie.glickman&jones.ps
    • (1999) AAAI-99 Workshop on Machine Learning for Information Extraction
    • Glickman, O.1    Jones, R.2
  • 13
    • 0003860888 scopus 로고    scopus 로고
    • Learning and Representing Topic: A Hierarchical Mixture Model for Word Occurrences in Document
    • Carnegie-Mellon University
    • Thomas Hofmann, 1998. "Learning and Representing Topic: A Hierarchical Mixture Model for Word Occurrences in Document," Conference for Automated Learning and Discovery, Workshop on Learning from Text and the Web, Carnegie-Mellon University, and at http://www.icsi.berkeley.edu/ ∼hofmann/
    • (1998) Conference for Automated Learning and Discovery, Workshop on Learning from Text and the Web
    • Hofmann, T.1
  • 19
    • 0000033413 scopus 로고    scopus 로고
    • Lexically-Generated Subject Hierarchies for Browsing Large Collections
    • Craig G. Nevill-Manning, Ian H. Witten, and Gordon W. Paynter, 1999. "Lexically-Generated Subject Hierarchies for Browsing Large Collections," International Journal of Digital Libraries, volume 2, number 3, pp. 111-123, and at http://sequence.rutgers.edu/∼nevill/
    • (1999) International Journal of Digital Libraries , vol.2 , Issue.3 , pp. 111-123
    • Nevill-Manning, C.G.1    Witten, I.H.2    Paynter, G.W.3
  • 20
    • 0003309997 scopus 로고    scopus 로고
    • Text Classification from Labeled and Unlabeled Documents using EM
    • in press
    • Kamil Nigam, Andrew McCallum, Sebastian Thrum, and Tom Mitchell, in press. "Text Classification from Labeled and Unlabeled Documents using EM," Machine Learning Journal, and at http://citeseer.nj.nec.com/pdf/14059
    • Machine Learning Journal
    • Nigam, K.1    McCallum, A.2    Thrum, S.3    Mitchell, T.4
  • 23
    • 0037891968 scopus 로고    scopus 로고
    • Extraction-Based Text Categorization: Generating Domain-specific Role Relationships Automatically
    • Tomek Strzalkowski (editor). Boston: Kluwer
    • E. Riloff and J. Lorenzen, 1999. "Extraction-Based Text Categorization: Generating Domain-specific Role Relationships Automatically," In: Tomek Strzalkowski (editor). Natural Language Information Retrieval. Boston: Kluwer, and at http://www.cs.utah.edu/ ∼riloff/psfiles/nlp-ir-chapter.ps
    • (1999) Natural Language Information Retrieval
    • Riloff, E.1    Lorenzen, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.