Name
Title | ||
|---|---|---|
An Adjusted Apriori Algorithm to Itemsets Defined by Tables and an Improved Rule Generator with Three-Way Decisions. |
Abstract | ||
|---|---|---|
The NIS-Apriori algorithm, which is extended from the Apriori algorithm, was proposed for rule generation from non-deterministic information systems and implemented in SQL. The realized system handles the concept of certainty, possibility, and three-way decisions. This paper newly focuses on such a characteristic of table data sets that there is usually a fixed decision attribute. Therefore, it is enough for us to handle itemsets with one decision attribute, and we can see that one frequent itemset defines one implication. We make use of these characteristics and reduce the unnecessary itemsets for improving the performance of execution. Some experiments by the implemented software tool in Python clarify the improved performance. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-3-030-52705-1_7 | IJCRS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwen Jian | 1 | 0 | 1.01 |
| Hiroshi Sakai | 2 | 0 | 0.34 |
| Takuya Ohwa | 3 | 0 | 0.34 |
| Kao-Yi Shen | 4 | 55 | 6.76 |
| Michinori Nakata | 5 | 292 | 37.49 |