Name
Abstract | ||
|---|---|---|
In this paper, we propose an effective rice crop planning system based on a knowledge engineering approach with hybrid knowledge representation, i.e., ontologies and rules, to help farmers make decisions in choosing their rice variety and planning cultivation. A critical challenge is to develop a recommendation system that supports and fulfills farmers' satisfaction, i.e., reducing risk from climate conditions and disease while improving productivity to meet market demand. To fulfill these needs, our recommendation system is separated into two parts: a rice variety suggestion system, which will help to suggest which variety to grow; and a personalized crop calendar generation system, which will help farmers in planning their activities toward higher production. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2857218.2857272 | MEDES |
Field | DocType | Citations |
Ontology (information science),Recommender system,Knowledge representation and reasoning,Computer science,Expert system,Knowledge management,Knowledge engineering,Supply and demand | Conference | 1 |
PageRank | References | Authors |
0.48 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| asanee kawtrakul | 1 | 161 | 25.90 |
| Rudeemas Amorntarant | 2 | 1 | 0.48 |
| Hutchatai Chanlekha | 3 | 56 | 4.89 |