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Record Nr. |
UNINA9910299679503321 |
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Autore |
Adhikari Animesh |
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Titolo |
Advances in Knowledge Discovery in Databases / / by Animesh Adhikari, Jhimli Adhikari |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (377 p.) |
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Collana |
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Intelligent Systems Reference Library, , 1868-4394 ; ; 79 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Data mining |
Artificial intelligence |
Computational Intelligence |
Data Mining and Knowledge Discovery |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Synthesizing conditional patterns in a database -- Synthesizing arbitrary Boolean expressions induced by frequent itemsets -- Measuring association among items in a database -- Mining association rules induced by item and quantity purchased -- Mining patterns different related databases -- Mining icebergs in different time-stamped data sources.-Synthesizing exceptional patterns in different data Sources -- Clustering items in time-stamped databases -- Synthesizing some extreme association rules from multiple databases -- Clustering local frequency items in multiple data sources -- Mining patterns of select items in different data sources -- Mining calendar-based periodic patterns in time-stamped data -- Measuring influence of an item in time-stamped databases -- Clustering multiple databases induced by local patterns -- Enhancing quality of patterns in multiple related databases -- Concluding remarks. |
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Sommario/riassunto |
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This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, |
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time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association measures are presented, which play significant roles in decision support applications. This book presents, discusses and contrasts new developments in mining time-stamped data, time-based data analyses, the identification of temporal patterns, the mining of multiple related databases, as well as local patterns analysis. . |
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