توضیحات
ABSTRACT
This paper presents a first step towards a unifying frameworkfor Knowledge Discovery in Databases. We describe finks betweendata milfing, knowledgediscovery, and other related fields. Wethen define the KDD process and basic data mining algorithms, discuss application issues and concludewith an analysis of challengesfacingpractitioners in the field.
INTRODUCTION
Acrossa wide variety of fields, data are being collected and accumulated at a dramatic pace. There is an urgent need for a new generation of computational techniques and tools to assist humansin extracting useful information (knowledge) from the rapidly growing volumes of data, These techniques and tools are the subject of the emerging field of knowledgediscovery in databases (KDD).This paper is an initial step towards a commonframework that we hope will allow us to understand the variety of activities in this multidisciplinary field and howthey fit together. Weview the knowledgediscovery process as a set of various activities for makingsense of data. At the core of this process is the application of data mining methodsfor pattern t discovery. Weexamine how data mining is used and outline someof its methods. Finally, we look at practical application issues of KDD and enumerate challenges for future research and development. Historically the notion of finding useful patterns in data has been given a variety of namesincluding data mining, knowledgeextraction, information discovery, information harvesting, data archaeology, and data pattern processing. The term data mining has been mostly used by statisticians, data analysts, and the ~Throughoutthis paper we use the term “pattern” to designate pattern or modelextracted fromthe data. management information systems (MIS) communities. It has also gained popularity in the database field. The term KDDwas coined at the first KDDworkshop in 1989 (Piatetsky- Shapiro 199t) to emphasize that “knowledge” is the end product of a data-driven discovery. It has beenpopularized in artificial intelligence and machine learning.
Year: 1996
Publishe: KDD
By: Usama Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth
File Information: English Language/ 7 Page / size:667KB
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سال : 1996
ناشر : KDD
کاری از : Usama Fayyad, Gregory Piatetsky-Shapiro, Padhraic Smyth
اطلاعات فایل : زبان انگلیسی / 7 صفحه / حجم : 667KB
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