Name
Abstract | ||
|---|---|---|
Determining minimum support value on association rule is not easy to users. Hurdles such as data locations and data origins are a mountain that should be overcome by association rule. In addition, rules generated do not necessarily fit user’s needs, thereby, requiring the rules to be put in order based on certain criteria. This paper will discuss a model to produce adaptive rules that originate from a number of different databases, automated threshold determination and rule ranking based on predetermined criteria. The adaptive rule model produced can be implemented in recommender systems in various fields. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.icte.2020.06.001 | ICT Express |
Keywords | DocType | Volume |
Adaptive rule,Association rule,Recommender system | Journal | 6 |
Issue | ISSN | Citations |
3 | 2405-9595 | 0 |
PageRank | References | Authors |
0.34 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erna Hikmawati | 1 | 0 | 0.34 |
| Nur Ulfa Maulidevi | 2 | 0 | 0.34 |
| Kridanto Surendro | 3 | 5 | 5.16 |