Mining Sequential Rules By Applying Sliding Window Constraint kitap kapağı
Kitap başlığı:

Mining Sequential Rules By Applying Sliding Window Constraint

Mining of Partially-Ordered Sequential Rules (POSR) By Applying the Sliding-Window Constraint

LAP LAMBERT Academic Publishing (2018-05-24 )

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ISBN-13:

978-613-9-84141-7

ISBN-10:
6139841410
EAN:
9786139841417
Kitabın dili:
İngilizce
Özet:
Sequential rule mining is used to extract important data in various application such as stock market analysis, e-commerce. It generally includes identifying sequential rules from given sequence database which will be common in multiple sequences. Partially Ordered Sequential rules (POSR) is a type of sequential rules in which the items in left and right side of the sequential rule does not need to be ordered. The existing approaches used for mining POSR include RuleGrowth Algorithm, TRuleGrowth Algorithm. But, these approaches either not use sliding window size constraint (RuleGrowth) or take more execution time even after using the sliding window size constraint (TRuleGrowth).This book presents a technique called M_TRuleGrowth which takes the sequence database as input and applies minimum support, minimum confidence, and window size constraints respectively to generate partially-ordered sequential rules. The experimental evaluation in terms of number of rules generated and execution time is conducted to compare the technique with existing approaches. It is found that the M_TRuleGrowth performs better in terms of execution time.
Yayınevi:
LAP LAMBERT Academic Publishing
Websitesi:
https://www.lap-publishing.com/
Yazar:
Sandipkumar Sagare
Sayfa sayısı:
64
Yayın tarihi:
2018-05-24
Hisse:
Mevcut
Kategori:
Other
Fiyat:
35.90 €
Anahtar kelimeler:
association rule, sequence, Sequential Pattern mining, Sequential Rule, Sequential Rule mining

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