Search (29 results, page 1 of 2)

  • × theme_ss:"Data Mining"
  • × year_i:[1990 TO 2000}
  1. KDD : techniques and applications (1998) 0.05
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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
  2. Howlett, D.: Digging deep for treasure (1998) 0.04
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    Date
    26. 3.2000 16:35:23
  3. Tunbridge, N.: Semiology put to data mining (1999) 0.04
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    Source
    Online and CD-ROM review. 23(1999) no.5, S.303-305
  4. Raghavan, V.V.; Deogun, J.S.; Sever, H.: Knowledge discovery and data mining : introduction (1998) 0.03
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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
    Date
    7. 2.1999 11:23:06
  5. Data mining : Theoretische Aspekte und Anwendungen (1998) 0.03
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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
    Series
    Beiträge zur Wirtschaftsinformatik; Bd.27
  6. Analytische Informationssysteme : Data Warehouse, On-Line Analytical Processing, Data Mining (1998) 0.01
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    Abstract
    Neben den operativen Informationssystemen treten heute verstärkt Informationssysteme für die analytischen Aufgaben der Fach- und Führungskräfte in den Vordergrund. In fast allen Unternehmen werden derzeit Begriffe und Konzepte wie Data Warehouse, On-Line Analytical Processing und Data Mining diskutiert und die zugehörigen Produkte evaluiert. Vor diesem Hintergrund zielt der vorliegende Sammelband darauf, einen aktuellen Überblick über Technologien, Produkte und Trends zu bieten. Als Entscheidungsgrundlage für den Praktiker beim Aufbau und Einsatz derartiger analytischer Informationssysteme können die unterschiedlichen Beiträge aus Wirtschaft und Wissenschaft wertvolle Hilfestellung leisten
  7. Analytische Informationssysteme : Data Warehouse, On-Line Analytical Processing, Data Mining (1999) 0.01
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    Abstract
    Neben den operativen Informationssystemen, welche die Abwicklung des betrieblichen Tagesgeschäftes unterstützen, treten heute verstärkt Informationssysteme für analytische Aufgaben der Fach- und Führungskräfte in den Vordergrund. In fast allen Unternehmen werden derzeit Begriffe und Konzepte wie Data Warehouse, On-Line Analytical Processing und Data Mining diskutiert und die zugehörigen Produkte evaluiert. Vor diesem Hintergrund zielt der vorliegende Sammelband darauf ab, einen aktuellen Überblick über Technologien, Produkte und Trends zu bieten. Als Entscheidungsgrundlage für den Praktiker beim Aufbau und Einsatz derartiger analytischer Informationssysteme können die unterschiedlichen Beiträge aus Wirtschaft und Wissenschaft wertvolle Hilfestellung leisten.
    Content
    Grundlagen.- Data Warehouse.- On-line Analytical Processing.- Data Mining.- Betriebswirtschaftliche und strategische Aspekte.
  8. Principles of data mining and knowledge discovery (1998) 0.01
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    Abstract
    The volume presents 26 revised papers corresponding to the oral presentations given at the conference, also included are refereed papers corresponding to the 30 poster presentations. These papers were selected from a total of 73 full draft submissions. The papers are organized in topical sections on rule evaluation, visualization, association rules and text mining, KDD process and software, tree construction, sequential and spatial data mining, and attribute selection
    Series
    Lecture notes in computer science; vol.1510
  9. 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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    Abstract
    Focuses on the information modelling side of conceptual modelling. Deals with the exploitation of fact verbalisations after finishing the actual information system. Verbalisations are used as input for the design of the so-called information model. Exploits these verbalisation in 4 directions: considers their use for a conceptual query language, the verbalisation of instances, the description of the contents of a database and for the verbalisation of queries in a computer supported query environment. Provides an example session with an envisioned tool for end user query formulations that exploits the verbalisation
    Source
    Information systems. 22(1997) nos.5/6, S.349-385
  10. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.00
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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
  11. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.00
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    Abstract
    Current algorithms for finding associations among the attributes describing data in a database have a number of shortcomings. Presents a novel method for association generation, that answers all desiderata. The method is different from all existing algorithms and especially suitable to textual databases with binary attributes. Uses subword trees for quick indexing into the required database statistics. Tests the algorithm on the Reuters-22173 database with satisfactory results
    Source
    Information systems. 22(1997) nos.5/6, S.333-347
  12. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.00
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    Date
    2. 4.2000 18:01:22
  13. Fayyad, U.; Piatetsky-Shapiro, G.; Smyth, P.: From data mining to knowledge discovery in databases (1996) 0.00
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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
  14. Advances in knowledge discovery and data mining (1996) 0.00
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    Footnote
    Rez. in: JASIS 49(1998) no.4, S.386-387 (F. Exner)
  15. Mattison, R.: Data warehousing and data mining for telecommunications (1997) 0.00
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    Footnote
    Rez. in: Database 21(1998) no.3, S.94 (J.D. Blackwell)
  16. Bell, D.A.; Guan, J.W.: Computational methods for rough classification and discovery (1998) 0.00
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    Abstract
    Rough set theory is a mathematical tool to deal with vagueness and uncertainty. To apply the theory, it needs to be associated with efficient and effective computational methods. A relation can be used to represent a decison table for use in decision making. By using this kind of table, rough set theory can be applied successfully to rough classification and knowledge discovery. Presents computational methods for using rough sets to identify classes in datasets, finding dependencies in relations, and discovering rules which are hidden in databases. Illustrates the methods with a running example from a database of car test results
  17. Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999) 0.00
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  18. Cardie, C.: Empirical methods in information extraction (1997) 0.00
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    Footnote
    Contribution to a special section reviewing recent research in empirical methods in speech recognition, syntactic parsing, semantic processing, information extraction and machine translation
  19. Gaizauskas, R.; Wilks, Y.: Information extraction : beyond document retrieval (1998) 0.00
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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
  20. Wong, S.K.M.; Butz, C.J.; Xiang, X.: Automated database schema design using mined data dependencies (1998) 0.00
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    Abstract
    Data dependencies are used in database schema design to enforce the correctness of a database as well as to reduce redundant data. These dependencies are usually determined from the semantics of the attributes and are then enforced upon the relations. Describes a bottom-up procedure for discovering multivalued dependencies in observed data without knowing a priori the relationships among the attributes. The proposed algorithm is an application of the technique designed for learning conditional independencies in probabilistic reasoning. A prototype system for automated database schema design has been implemented. Experiments were carried out to demonstrate both the effectiveness and efficiency of the method