Search (19 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Data Mining"
  • × year_i:[1990 TO 2000}
  1. Cardie, C.: Empirical methods in information extraction (1997) 0.04
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    Date
    6. 3.1999 13:50:29
    Footnote
    Contribution to a special section reviewing recent research in empirical methods in speech recognition, syntactic parsing, semantic processing, information extraction and machine translation
  2. Galal, G.M.; Cook, D.J.; Holder, L.B.: Exploiting parallelism in a structural scientific discovery system to improve scalability (1999) 0.03
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    Abstract
    The large amount of data collected today is quickly overwhelming researchers' abilities to interpret the data and discover interesting patterns. Knowledge discovery and data mining approaches hold the potential to automate the interpretation process, but these approaches frequently utilize computationally expensive algorithms. In particular, scientific discovery systems focus on the utilization of richer data representation, sometimes without regard for scalability. This research investigates approaches for scaling a particular knowledge discovery in databases (KDD) system, SUBDUE, using parallel and distributed resources. SUBDUE has been used to discover interesting and repetitive concepts in graph-based databases from a variety of domains, but requires a substantial amount of processing time. Experiments that demonstrate scalability of parallel versions of the SUBDUE system are performed using CAD circuit databases and artificially-generated databases, and potential achievements and obstacles are discussed
    Source
    Journal of the American Society for Information Science. 50(1999) no.1, S.65-73
  3. Gaizauskas, R.; Wilks, Y.: Information extraction : beyond document retrieval (1998) 0.02
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    Abstract
    In this paper we give a synoptic view of the growth of the text processing technology of informatione xtraction (IE) whose function is to extract information about a pre-specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining
  4. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.02
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    Date
    5. 4.1996 15:29:15
    Source
    Information systems. 22(1997) nos.5/6, S.333-347
  5. Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997) 0.01
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    Date
    5. 4.1996 15:29:15
    Source
    Information systems. 22(1997) nos.5/6, S.349-385
  6. Methodologies for knowledge discovery and data mining : Third Pacific-Asia Conference, PAKDD'99, Beijing, China, April 26-28, 1999, Proceedings (1999) 0.01
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    Abstract
    The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization, causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies
    Series
    Lecture notes in computer science; vol.1574
  7. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.01
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    Date
    2. 4.2000 18:01:22
  8. KDD : techniques and applications (1998) 0.01
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    Footnote
    A special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
  9. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.00
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    Date
    22.11.1998 18:57:22
  10. Knowledge discovery and data mining (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.397-470
  11. Fayyad, U.M.; Djorgovski, S.G.; Weir, N.: From digitized images to online catalogs : data ming a sky server (1996) 0.00
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    Abstract
    Offers a data mining approach based on machine learning classification methods to the problem of automated cataloguing of online databases of digital images resulting from sky surveys. The SKICAT system automates the reduction and analysis of 3 terabytes of images expected to contain about 2 billion sky objects. It offers a solution to problems associated with the analysis of large data sets in science
  12. Principles of data mining and knowledge discovery (1998) 0.00
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    Series
    Lecture notes in computer science; vol.1510
  13. Trybula, W.J.: Data mining and knowledge discovery (1997) 0.00
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    Source
    Annual review of information science and technology. 32(1997), S.197-229
  14. Wong, S.K.M.; Butz, C.J.; Xiang, X.: Automated database schema design using mined data dependencies (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.455-470
  15. Raghavan, V.V.; Deogun, J.S.; Sever, H.: Knowledge discovery and data mining : introduction (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.397-402
  16. Bell, D.A.; Guan, J.W.: Computational methods for rough classification and discovery (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.403-414
  17. Lingras, P.J.; Yao, Y.Y.: Data mining using extensions of the rough set model (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.415-422
  18. Deogun, J.S.: Feature selection and effective classifiers (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.423-434
  19. Wu, X.: Rule induction with extension matrices (1998) 0.00
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    Source
    Journal of the American Society for Information Science. 49(1998) no.5, S.435-454