More formally, let / = (ih i'2 im) be a set of literals, called items. Let D be a set of transactions, where each transaction T is a set of items such that T c /• Each item is a binary variable representing whether an item was bought. Data Mining, Southeast Asia Edition - Page 230by Jiawei Han, Jian Pei, Micheline Kamber - 2006 - 800 pagesLimited preview - About this book
| Takushi Tanaka, Moonis Ali, Setsuo Ohsuga - 1997 - 838 pages
...formalism presented in [AS94]. Let / = {i,./2,...,(m} be a set of literals, called items. Let/) be a set of transactions, where each transaction T is a set of items such that re/. Associated with each transaction is a unique identifier, called its TID. We say that a transaction... | |
| Rodney Topor, Katsumi Tanaka - 1997 - 567 pages
...association rules Let / = {ii,»z, ... 1 tm} be a set of literals, called items. Let D be a database of transactions, where each transaction T is a set of items such that TCI. For a given itemset XC / and a given transaction T, we say that T contains X if and only if XC T. The... | |
| Hung Dang Van - 2002 - 452 pages
...distinct literals, called items. In general, any set of items is called an itemset. Let 2> be a set of transactions, where each transaction T is a set of items such that T c /. An association rule is an expression of the form X => Y, where 0 * X,Y c / and X n Y = 0. X... | |
| Pavol Návrat, Haruki Ueno - 1998 - 340 pages
...= {i t , i2, .... i m \ be a set of literals, called items. Let D = {TV, T 2 , .... TV} be a set of transactions, where each transaction T, is a set of items such that T, e /. Associated with each transaction is a unique identifier, called its TID. A set of items X c... | |
| Zbigniew W. Ras, Andrzej Skowron - 1999 - 700 pages
...distinct literals, called items. In general, any set of items is called an itemset. Let D be a set of transactions, where each transaction T is a set of items such that T c /. An association rule is an expression of the form: X => Y, where 0 *X,Y c /and X n Y = 0. X is... | |
| Roland T. Rust, P. K. Kannan - 2002 - 352 pages
...al. 1993; Agrawal and Srikant 1994). Let / {i„ J 2 ,... ,i m ) be a set of items. Let D be a set of transactions, where each transaction T is a set of items such that T c/. In the recommendation context, each transaction corresponds to a user and contains a set of items... | |
| Michael R. Berthold, David J Hand - 2007 - 515 pages
...transactions in which the items co-occur. Let / = {ii, ...in} be a set of items and let D be a set of transactions, where each transaction T is a set of items such that TCI. An association rule is an implication of the form X =^ Y, where XCI, Y 6 /, X, Y ^ 0. The confidence... | |
| Olivier Camp - 2004 - 354 pages
...the relativity. 2.2 Association Mining Let I=)il. i2 im}bea set of items. Let D, the task relevant data, be a set of database transactions where each transaction T is a set of items such that TC I. Each transaction is associated with an identifier, called TID. Let A be a set of items. A transaction... | |
| Charles D. Hansen, Chris R. Johnson - 2005 - 1062 pages
...transactions in which the items co-occur. Let / = {z'i, .../„} be a set of items and let D be a set of transactions, where each transaction T is a set of items such that TCI. An association rule is an implication of the form X => Y, where X e /, Y e /, and X, 7^0. The confidence... | |
| AJOY KUMAR RAY, TINKU ACHARYA - 2004 - 640 pages
...association rules. Let 7 = {ilt i%, ..., im] be a set of literals, called items. Let D be a set of transactions, where each transaction T is a set of items such that T c 7. Note that the quantities of items bought in a transaction are not considered, meaning that each... | |
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