Name
Title | ||
|---|---|---|
Mining Association Rules from Market Basket Data using Share Measures and Characterized Itemsets |
Abstract | ||
|---|---|---|
The problem of mining association rules from market basket data has recently been an important research topic in the area of knowledge discovery from databases. It was originally introduced in [2] and studied extensively in [1, 5, 25, 26, 31, 19, 23, 29, 30, 3, 4, 33, 14]. The problem is typically examined in the context of discovering buying patterns from retail sales transactions. Although there are many similar data mining applications which can be modelled in this way, we again study the... |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1142/S0218213098000111 | International Journal on Artificial Intelligence Tools |
Keywords | Field | DocType |
knowledge discovery,association rule,machine learning,association rules,data mining | Data mining,Market basket,Computer science,Apriori algorithm,Association rule learning,Knowledge extraction,Hierarchy | Journal |
Volume | Issue | Citations |
7 | 2 | 19 |
PageRank | References | Authors |
2.27 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert J. Hilderman | 1 | 270 | 29.86 |
| Howard J. Hamilton | 2 | 1501 | 145.55 |
| Colin L. Carter | 3 | 66 | 5.88 |
| Nick Cercone | 4 | 1999 | 570.62 |