Frequent Pattern Mining in Transactional and Structured Databases | Different aspects of itemset, sequence and subtree discovery

Renáta Iváncsy

ISBN 10: 3843359741 / ISBN 13: 9783843359740

Published by LAP LAMBERT Academic Publishing, 2010

About this Item

Frequent Pattern Mining in Transactional and Structured Databases | Different aspects of itemset, sequence and subtree discovery | Renáta Iváncsy | Taschenbuch | 144 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783843359740 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 107273346

Bibliographic Details

• Title: Frequent Pattern Mining in Transactional and Structured Databases | Different aspects of itemset, sequence and subtree discovery
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2010
• Language: English
• ISBN 10: 3843359741
• ISBN 13: 9783843359740
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 10D millimeters 220 millimeters width by 150 millimeters height by 10 millimeters depth
• Weight: 233 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Data mining is a process of discovering hidden relationships in large amounts of data. Frequent pattern discovery is an important research area in the field of data mining. Its purpose is to find patterns which appear frequently in a large collection of data. This work deals with three main areas of frequent pattern mining, namely, frequent itemset, frequent sequence and frequent subtree discovery. Beside providing a brief overview of related works of each single frequent pattern mining problem mentioned before, the three theses offered in this work suggest novel methods for efficient discovery of the different types of frequent patterns. The new methods are compared to the best-known algorithms in the related fields. The performance analysis of the methods involves measurements of the execution time and memory requirements.

About the Author

Renáta Iváncsy received her Ph.D degree in 2006. She is Associate Proffesor at Department of Automation and Applied Informatics of the Budapest University of Technology and Economics. Her research field is data mining, particularly frequent pattern discovery, clustering and text data mining.