An Expert System Using Ontology as Knowledge Base for Personalized Rice Cultivation Suggestion

被引：0

作者：

Chariyamakarn, Wichuphon ^{[1
]}

Boonbrahm, Poonpong ^{[1
]}

Boonbrahm, Salin ^{[1
]}

Ruangrajitpakorn, Taneth ^{[2
,3
]}

机构：

[1] Walailak Univ, Sch Informat, Nakorn Si Thammarat, Thailand

[2] Thammasat Univ, Dept Comp Sci, Pathum Thani, Thailand

[3] Nation Elect & Comp Technol Ctr NECTEC, Language & Semant Technol Lab, Pathum Thani, Thailand

来源：

RECENT ADVANCES AND FUTURE PROSPECTS IN KNOWLEDGE, INFORMATION AND CREATIVITY SUPPORT SYSTEMS | 2018年 / 685卷

关键词：

Expert system; Rice production; Reasoning based recommendation; Automatic suggestion; Ontology; USER-CENTERED ONTOLOGY; FARMERS;

D O I：

10.1007/978-3-319-70019-9_11

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work presents a framework to assist Thai rice farmers in cultivation planning. Knowledge of rice production is extracted from best practice documents and kept in ontology. Concepts relevant to rice production such as soil type of every location in Thailand and rice seeds with their strong and weak properties are semantically drawn in the ontology. The ontology associated with rules to make decision is exploited as a knowledge base for the system to infer a reasonable suggestion based on farmers' specific information, context and need. According to farmers input, different suggestions can be given including seed selection, land preparation, concern in cultivation based on preferred seed, etc. From testing, the generated recommendations were satisfied by rice production experts for precise criteria analysis and proper reason selection in inference process. An experiment result of seed selection showed that the system generated suggestions with 0.56 precision score and 0.97 recall score comparing to human expert suggestions.

引用

页码：126 / 140

页数：15

共 50 条

[41] HESTool: An expert system tool based on hierarchical knowledge base
Cao, Z.-W.
Zhu, C.
Liu, Z.
Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2001, 23 (03): : 120 - 124
[42] Fuzzy expert system with double knowledge base for ultrasonic classification
Llata, JR
Sarabia, EG
Oria, JP
EXPERT SYSTEMS WITH APPLICATIONS, 2001, 20 (04) : 347 - 355
[43] A METHOD OF EXPERT CLASSIFICATION FOR THE DIAGNOSTIC SYSTEM KNOWLEDGE BASE DEVELOPMENT
LARICHEV, OI
MECHITOV, AI
MOSHKOVICH, EM
FUREMS, EM
DOKLADY AKADEMII NAUK SSSR, 1988, 298 (05): : 1086 - 1089
[44] Module to Generate Rules for the Knowledge Base in a CAPCAST Expert System
Mrzyglod, B.
Scira, K.
ARCHIVES OF FOUNDRY ENGINEERING, 2012, 12 (02) : 167 - 170
[45] 'OAL' guidelines as the knowledge base for an integrative acoustical expert system
Mahdavi, A.
Inter-Noise: Proceedings, 1992, 2
[46] Expert System for Predictive Diagnosis (1) Principles and Knowledge Base
Isoc, Dorin
SOFT COMPUTING APPLICATIONS, SOFA 2016, VOL 1, 2018, 633 : 18 - 33
[47] Expert system of weld crack diagnosis based on knowledge base
Zhu, Y.
Zhang, Y.
Sun, Q.
Li, X.
Hanjie Xuebao/Transactions of the China Welding Institution, 2001, 22 (03): : 59 - 62
[48] Generating Personalized Explanations for Recommender Systems Using a Knowledge Base
Chen, Yuhao
Luo, Shi-Jun
Han, Hyoil
Miyazaki, Jun
Saldanha, Alfrin Letus
INTERNATIONAL JOURNAL OF MULTIMEDIA DATA ENGINEERING & MANAGEMENT, 2021, 12 (04): : 20 - 37
[49] USING PUBLIC DOMAIN SOFTWARE TO DEVELOP AN EXPERT SYSTEM - A BUSINESS REFERENCE SOURCES KNOWLEDGE BASE
ALBERICO, R
LIBRARY SOFTWARE REVIEW, 1988, 7 (03): : 190 - 191
[50] Building an ontology and knowledge base of the human meridian-collateral system
Cao, CG
Sui, YF
APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XIII, 2006, : 195 - +

← 1 2 3 4 5 →