Association Rule Mining in XML Database - Couverture souple

Duraisamy, Sasikala; Kandasamy, Premalatha

 
9786202072427: Association Rule Mining in XML Database
Couverture souple
ISBN 10 : 6202072423 ISBN 13 : 9786202072427
Editeur : LAP LAMBERT Academic Publishing, 2018

Synopsis

Data mining is a process of extracting hidden information from large databases. It is a powerful technology that helps to analyze the important information present in the databases. Association Rule Mining (ARM) is a research field in data mining that extracts frequent patterns of items in the transaction databases. In order to select interesting rules from the set of all possible rules, various measures are used. The two basic interestingness measures in ARM are support and confidence. In addition to market basket analysis association rules are applied in the areas including web usage mining, intrusion detection, and bioinformatics.

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Présentation de l'éditeur

Data mining is a process of extracting hidden information from large databases. It is a powerful technology that helps to analyze the important information present in the databases. Association Rule Mining (ARM) is a research field in data mining that extracts frequent patterns of items in the transaction databases. In order to select interesting rules from the set of all possible rules, various measures are used. The two basic interestingness measures in ARM are support and confidence. In addition to market basket analysis association rules are applied in the areas including web usage mining, intrusion detection, and bioinformatics.

Biographie de l'auteur

Dr. D. Sasikala completed her undergraduate degree in Computer Science at Bharathiyar University,Coimbatore in 2000 and she has 17 years of teaching experience. She completed her Ph.D in 2016. Currently she is working as Associate Professor in the Department of CSE at Bannari Amman Institute of Technology, Sathy, Erode.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2018
Langue
anglais
ISBN 10 
6202072423
ISBN 13 
9786202072427
Reliure
Broché
Nombre de pages
56
Coordonnées du fabricant
non disponible
Personne responsable
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