Search (23 results, page 1 of 2)

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

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

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

Tunbridge, N.: Semiology put to data mining (1999) 0.10

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Theme: Data Mining

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

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

Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999) 0.09

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Theme: Data Mining

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

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

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

Howlett, D.: Digging deep for treasure (1998) 0.07

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Theme: Data Mining

Lingras, P.J.; Yao, Y.Y.: Data mining using extensions of the rough set model (1998) 0.07
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Abstract

Examines basic issues of data mining using the theory of rough sets, which is a recent proposal for generalizing classical set theory. The Pawlak rough set model is based on the concept of an equivalence relation. A generalized rough set model need not be based on equivalence relation axioms. The Pawlak rough set model has been used for deriving deterministic as well as probabilistic rules froma complete database. Demonstrates that a generalised rough set model can be used for generating rules from incomplete databases. These rules are based on plausability functions proposed by Shafer. Discusses the importance of rule extraction from incomplete databases in data mining

Footnote

Contribution to a special issue devoted to knowledge discovery and data mining

Theme

Data Mining
Trybula, W.J.: Data mining and knowledge discovery (1997) 0.06
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Abstract

State of the art review of the recently developed concepts of data mining (defined as the automated process of evaluating data and finding relationships) and knowledge discovery (defined as the automated process of extracting information, especially unpredicted relationships or previously unknown patterns among the data) with particular reference to numerical data. Includes: the knowledge acquisition process; data mining; evaluation methods; and knowledge discovery. Concludes that existing work in the field are confusing because the terminology is inconsistent and poorly defined. Although methods are available for analyzing and cleaning databases, better coordinated efforts should be directed toward providing users with improved means of structuring search mechanisms to explore the data for relationships

Theme

Data Mining
Wu, X.: Rule induction with extension matrices (1998) 0.05
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Abstract

Presents a heuristic, attribute-based, noise-tolerant data mining program, HCV (Version 2.0), absed on the newly-developed extension matrix approach. Gives a simple example of attribute-based induction to show the difference between the rules in variable-valued logic produced by HCV, the decision tree generated by C4.5 and the decision tree's decompiled rules by C4.5 rules. Outlines the extension matrix approach for data mining. Describes the HCV algorithm in detail. Outlines techniques developed and implemented in the HCV program for noise handling and discretization of continuous domains respectively. Follows these with a performance comparison of HCV with famous ID3-like algorithms including C4.5 and C4.5 rules on a collection of standard databases including the famous MONK's problems

Footnote

Contribution to a special issue devoted to knowledge discovery and data mining

Theme

Data Mining

Fayyad, U.M.; Djorgovski, S.G.; Weir, N.: From digitized images to online catalogs : data ming a sky server (1996) 0.05

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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
Theme: Data Mining

Chen, Z.: Knowledge discovery and system-user partnership : on a production 'adversarial partnership' approach (1994) 0.05
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Abstract

Examines the relationship between systems and users from the knowledge discovery in databases or data mining perspecitives. A comprehensive study on knowledge discovery in human computer symbiosis is needed. Proposes a database-user adversarial partnership, which is general enough to cover knowledge discovery and security of issues related to databases and their users. It can be further generalized into system-user adversarial paertnership. Discusses opportunities provided by knowledge discovery techniques and potential social implications

Theme

Data Mining

Wong, S.K.M.; Butz, C.J.; Xiang, X.: Automated database schema design using mined data dependencies (1998) 0.04

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Footnote: Contribution to a special issue devoted to knowledge discovery and data mining
Theme: Data Mining

Bell, D.A.; Guan, J.W.: Computational methods for rough classification and discovery (1998) 0.04

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Footnote: Contribution to a special issue devoted to knowledge discovery and data mining
Theme: Data Mining

Search tools (1997) 0.04
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Abstract

Offers brief accounts of Internet search tools. Covers the Lycos revamp; the new navigation service produced jointly by Excite and Netscape, delivering a language specific, locally relevant Web guide for Japan, Germany, France, the UK and Australia; InfoWatcher, a combination offline browser, search engine and push product from Carvelle Inc., USA; Alexa by Alexa Internet and WBI from IBM which are free and provide users with information on how others have used the Web sites which they are visiting; and Concept Explorer from Knowledge Discovery Systems, Inc., California which performs data mining from the Web, Usenet groups, MEDLINE and the US Patent and Trademark Office patent abstracts

Theme

Data Mining

Deogun, J.S.: Feature selection and effective classifiers (1998) 0.04

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Footnote: Contribution to a special issue devoted to knowledge discovery and data mining
Theme: Data Mining

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