Search (1411 results, page 1 of 71)

  • × year_i:[1990 TO 2000}
  1. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.22 
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    Date
    2. 4.2000 18:01:22
    Theme
    Data Mining
  2. KDD : techniques and applications (1998) 0.19 
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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
    Theme
    Data Mining
  3. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.17 
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    Date
    17. 7.2002 19:22:06
    RSWK
    Data mining / Lehrbuch
    Subject
    Data mining / Lehrbuch
    Theme
    Data Mining
  4. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.13 
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    Abstract
    Defines digital libraries and discusses the effects of new technology on librarians. Examines the different viewpoints of librarians and information technologists on digital libraries. Describes the development of a digital library at the National Drug Intelligence Center, USA, which was carried out in collaboration with information technology experts. The system is based on Web enabled search technology to find information, data visualization and data mining to visualize it and use of SGML as an information standard to store it
    Date
    22.11.1998 18:57:22
    Theme
    Data Mining
  5. Saz, J.T.: Perspectivas en recuperacion y explotacion de informacion electronica : el 'data mining' (1997) 0.11 
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    Abstract
    Presents the concept and the techniques identified by the term data mining. Explains the principles and phases of developing a data mining process, and the main types of data mining tools
    Footnote
    Übers. des Titels: Perspectives on the retrieval and exploitation of electronic information: data mining
    Theme
    Data Mining
  6. Tunbridge, N.: Semiology put to data mining (1999) 0.10 
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    Theme
    Data Mining
  7. Spertus, E.: ParaSite : mining structural information on the Web (1997) 0.10 
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    Date
    1. 8.1996 22:08:06
  8. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.10 
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    Source
    Information systems. 22(1997) nos.5/6, S.333-347
    Theme
    Data Mining
  9. Lawson, M.: Automatic extraction of citations from the text of English-language patents : an example of template mining (1996) 0.10 
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    Abstract
    Describes and evaluates methods for automatically isolating and extracting biliographic references from the full texts of patents, designed to facilitate the work of patent examiners who currently perform this task manually. These references include citations both to patents and to other bibliographic sources. Notes that patents are unusual as citing documents in that the citations occur maily in the body of the text, rather than as footnotes or in separate sections. Describes the natural language processing technique of template mining used to extract data directly from the text where either the data or the text surrounding the data form recognizable patterns. When text matches a template, the system extracts data according to instructions associated with that template. Examines the sub languages of citations and the development of templates for the extraction of citations to patent. Reports results of running 2 reference extraction systems against a sample of 100 European Patent Office patent documents, with recall and prescision data for patent and non patent citations, and concludes with suggestions for future improvements
    Source
    Journal of information science. 22(1996) no.6, S.423-436
  10. Li, D.: Knowledge representation and discovery based on linguistic atoms (1998) 0.10 
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    Abstract
    Describes a new concept of linguistic atoms with 3 digital characteristics: expected value Ex, entropy En, and deviation D. The mathematical description has effectively integrated the fuzziness and randomness of linguistic terms in a unified way. Develops a method of knowledge representation in KDD, which bridges the gap between quantitative and qualitative knowledge. Mapping between quantities and qualities becomes much easier and interchangeable. In order to discover generalised knowledge from a database, uses virtual linguistic terms and cloud transfer for the auto-generation of concept hierarchies to attributes. Predicitve data mining with the cloud model is given for implementation. Illustrates the advantages of this linguistic model in KDD
    Footnote
    Contribution to 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
  11. Data mining : Theoretische Aspekte und Anwendungen (1998) 0.09 
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    Abstract
    Behandelt werden u.a. die Themen: Ziele und Methoden des Data Mining, Prozeß der Wissensentdeckung, State of the Art in der Forschung und Anwendung des Data Mining, wichtige Data Mining Tools, die Rolle der Informationsverarbeitung im KDD Prozeß, Data Warehousing, OLAP, Ansätze zur Benutzerunterstüzung des Data Mining Prozesses, Modellselektion und Evaluierungsmethoden für Data Mining Algorithmen
    Theme
    Data Mining
  12. Knowledge discovery and data mining (1998) 0.09 
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    Footnote
    A special issue devoted to knowledge discovery and data mining
    Theme
    Data Mining
  13. Fayyad, U.; Piatetsky-Shapiro, G.; Smyth, P.: From data mining to knowledge discovery in databases (1996) 0.09 
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    Abstract
    Gives an overview of data mining and knowledge discovery in databases. Clarifies how they are related both to each other and to related fields. Mentions real world applications data mining techniques, challenges involved in real world applications of knowledge discovery, and current and future research directions
    Theme
    Data Mining
  14. Mattison, R.: Data warehousing and data mining for telecommunications (1997) 0.09 
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    Theme
    Data Mining
  15. Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999) 0.09 
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    Theme
    Data Mining
  16. Koczkodaj, W.: ¬A note on using a consistency-driven approach to CD-ROM selection (1997) 0.09 
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    Abstract
    As with print collections, the evaluation and selection of CD-ROMs should be based on established guidelines. Such attributes as computer network compatibility and platform are exclusively applicable to CD-ROM. Presents a knowledge based system to prioritize and select CD-ROMs for a library collection, operating on consistency driven pairwise comparisons. The computer system indicates the most inconsistent judgements and allows librarians to reconsider their position. After consistency analysis is completed, the software computes the weights of all criteria used in the evaluation process. The system includes a subsystem for evaluating CD-ROM titles. Offers a CD-ROM evaluation form. Discusses cost considerations; the use of pairwise comparisons in knowledge based systems with reference to data mining; the CD-ROM selection process; and consistency analysis of experts' judgements
    Date
    6. 3.1997 16:22:15
  17. Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997) 0.09 
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    Source
    Information systems. 22(1997) nos.5/6, S.349-385
    Theme
    Data Mining
  18. Cheung, D.W.; Kao, B.; Lee, J.: Discovering user access patterns on the World Wide Web (1998) 0.09 
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    Footnote
    Contribution to 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
  19. Raghavan, V.V.; Deogun, J.S.; Sever, H.: Knowledge discovery and data mining : introduction (1998) 0.08 
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    Abstract
    Defines knowledge discovery and database mining. The challenge for knowledge discovery in databases (KDD) is to automatically process large quantities of raw data, identifying the most significant and meaningful patterns, and present these as as knowledge appropriate for achieving a user's goals. Data mining is the process of deriving useful knowledge from real world databases through the application of pattern extraction techniques. Explains the goals of, and motivation for, research work on data mining. Discusses the nature of database contents, along with problems within the field of data mining
    Footnote
    Contribution to a special issue devoted to knowledge discovery and data mining
    Theme
    Data Mining
  20. Fayyad, U.M.: Data mining and knowledge dicovery : making sense out of data (1996) 0.08 
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    Abstract
    Defines knowledge discovery and data mining (KDD) as the overall process of extracting high level knowledge from low level data. Outlines the KDD process. Explains how KDD is related to the fields of: statistics, pattern recognition, machine learning, artificial intelligence, databases and data warehouses
    Theme
    Data Mining

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