Insight into interface design of web-based case-based reasoning retrieval systems

2009 ◽  
Vol 36 (3) ◽  
pp. 7280-7287 ◽  
Author(s):  
Wu He ◽  
Feng-Kwei Wang ◽  
Tawnya Means ◽  
Li Da Xu
Keyword(s):  
Interface Design ◽  
Case Based Reasoning ◽  
Web Based ◽  
Retrieval Systems ◽  
Insight Into ◽  
Case Based

Simplifying decision trees: A survey

1997 ◽  
Vol 12 (01) ◽  
pp. 1-40 ◽  
Author(s):  
LEONARD A. BRESLOW ◽  
DAVID W. AHA
Keyword(s):  
Decision Trees ◽  
Data Structures ◽  
Classification Accuracy ◽  
Case Based Reasoning ◽  
Reasoning Systems ◽  
Tree Generation ◽  
Good Classification ◽  
Classification Tasks ◽  
Insight Into ◽  
Case Based

Induced decision trees are an extensively-researched solution to classification tasks. For many practical tasks, the trees produced by tree-generation algorithms are not comprehensible to users due to their size and complexity. Although many tree induction algorithms have been shown to produce simpler, more comprehensible trees (or data structures derived from trees) with good classification accuracy, tree simplification has usually been of secondary concern relative to accuracy, and no attempt has been made to survey the literature from the perspective of simplification. We present a framework that organizes the approaches to tree simplification and summarize and critique the approaches within this framework. The purpose of this survey is to provide researchers and practitioners with a concise overview of tree-simplification approaches and insight into their relative capabilities. In our final discussion, we briefly describe some empirical findings and discuss the application of tree induction algorithms to case retrieval in case-based reasoning systems.

scholarly journals Analisis Penyakit Pada Tanaman Cabai Dengan Metode Case Based Reasoning Berbasis Web

2021 ◽  
Vol 1 (1) ◽  
pp. 43-48
Author(s):  
Desi Ernawati ◽  
Riki Andri Yusda ◽  
Guntur Maha Putra
Keyword(s):  
Expert System ◽  
Plant Diseases ◽  
Case Based Reasoning ◽  
Good Care ◽  
Web Based ◽  
Case Base ◽  
Case Base Reasoning ◽  
Case Based

Abstract:Chili is a production cropthatis much needed by the  community. Good care is needed to increase the production of chili plants. Production of chili plants will decrease if the types of diseases that attack are not considered. To find out about chili plant diseases, farmers only look at the disease without knowing the symptoms that appear beforehand so that it will affect the production of chili plants.So that we need experts who understand the symptoms of disease in chili plants.The existence of experts can be replaced by a system designed to detect symptoms of disease in chili plants.The expert system to be designed is web-based using the case-based reasoning method.This expert system is expected to help increase the productivity of chili plants.            Keywords:expert system; chili; case-based reasoning; chili plants.  Abstrak:Cabai merupakan tanaman produksi yang banyak dibutuhkan oleh masyarakat. Untuk meningkatkan produksi tanaman cabai diperlukan perawatan yang baik. Produksi dari tanaman cabai akan menurun jika tidak diperhatikan jenis penyakit yang menyerang. Untuk mengetahui penyakit tanaman cabai para petani hanya melihat penyakitnya saja tanpa mengetahui terlebih dahulu gejala yang muncul sehingga akan mempengaruhi hasil produksi tanaman cabai. Sehingga diperlukan pakar yang mengerti mengenai gejala penyakit pada tanaman cabai. Keberadaan pakar bisa digantikan oleh sebuah sistem yang dirancang untuk mendeteksi gejala penyakit pada tanaman cabai. Sistem pakar yang akan dirancang berbasis web dengan menggunakan metode case base reasoning. Sistem pakar ini nantinya diharapkan membantu untuk peningkatan produktivitas tanaman cabai. Kata kunci:sistem pakar; cabai; casebasereasoning; tanaman cabai.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2008 ◽  
pp. 2659-2672
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2004 ◽  
pp. 47-64 ◽  
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

Applying a case-based reasoning method for fault diagnosis during maintenance

2009 ◽  
Vol 223 (10) ◽  
pp. 2431-2441 ◽  
Author(s):  
Y-T Tsai
Keyword(s):  
Fault Diagnosis ◽  
Flow Analysis ◽  
Fault Tree Analysis ◽  
Case Based Reasoning ◽  
Web Based ◽  
Information Flow Analysis ◽  
Microsoft Access ◽  
System A ◽  
Moulding Machine ◽  
Case Based

The development of a fault-diagnosis system (FDS) could be helpful in identifying the source of faults before the occurrence of complete system failure. Here we report on such a diagnostic procedure for narrowing down maintenance tasks and shortening system downtime. A web-based FDS is developed based on case-based reasoning (CBR) from previous maintenance experience, for an injection moulding machine (IMM). The techniques of fault tree analysis (FTA) and information flow analysis are introduced to systematically clarify possible faults and symptoms shown by a system. A logical process is introduced to determine the correlation between the possible faults and the symptoms for computing case similarity while progressing CBR diagnosing. Some frontpages are developed for the CBR diagnosis using an ASP program in cooperation with a Microsoft Access database. The resultant FDS achieves good results with the potential for supporting remote IMM maintenance.

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