Reflective Reasoning in a Case-Based Reasoning Agent

1999 ◽  
pp. 142-158 ◽  
Author(s):  
Miquel Sànchez-Marrè ◽  
Ulises Cortés ◽  
Javier Béjar ◽  
Ignasi R. Roda ◽  
Manel Poch
Keyword(s):  
Case Based Reasoning ◽  
Reflective Reasoning ◽  
Reasoning Agent ◽  
Case Based

scholarly journals A Web Services, Ontology and Big Data Analysis Technology-Based Cloud Case-Based Reasoning Agent for Energy Conservation of Sustainability Science

2020 ◽  
Vol 10 (4) ◽  
pp. 1387
Author(s):  
Shih-Chin Chen ◽  
Sheng-Yuan Yang
Keyword(s):  
Big Data ◽  
Web Services ◽  
Energy Conservation ◽  
Energy Saving ◽  
Sustainability Science ◽  
Big Data Analytics ◽  
Case Based Reasoning ◽  
Core Technology ◽  
Reasoning Agent ◽  
Case Based

Energy conservation is one of the important topics for sustainability science, while case-based reasoning is one of the most important techniques for sustainable processing. This study aimed to develop a cloud case-based reasoning agent that integrates multiple intelligent technologies and supports, which can help users to quickly, accurately, and effectively obtain useful cloud energy-saving information in a timely manner for sustainability science. The system was successfully built with the support of Web services technology, ontology, and big data analytics. To set up this energy-saving case-based reasoning agent, this study reviewed the relevant technologies for building a web services platform and explored how to widely integrate and support the cloud interaction of the energy-saving data processing agent via the technologies. In addition to presenting relevant R&D technologies and results in detail, this study carefully conducted performance and learning experiments to prove the system’s effectiveness. The results showed that the core technology of the case-based reasoning agent achieved good performance and that the learning effectiveness of the overall system was also great.

Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Classification Problem ◽  
Subject Area ◽  
Text Messages ◽  
Case Based Reasoning ◽  
Short Text ◽  
Proposed Modification ◽  
Voice Interaction ◽  
Text Content ◽  
Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

Feature level intentions based product recommendations with case-based reasoning

2018 ◽  
Vol 6 (1) ◽  
pp. 266-274
Author(s):  
D. Teja Santosh ◽  
◽  
K.C. Ravi Kumar ◽  
P. Chiranjeevi ◽  
◽  
...  
Keyword(s):  
Case Based Reasoning ◽  
Product Recommendations ◽  
Case Based

SISTEM PAKAR UNTUK DIAGNOSA PENYAKIT ANAK DENGAN METODE CASE-BASED REASONING DENGAN ALGORITMA SIMILARITY JACCARD PADA PUSKESMAS HALMAHERA SEMARANG

2020 ◽  
Vol 11 (2) ◽  
pp. 57-63
Author(s):  
Didik Trisulo ◽  
Setyawan Wibisono
Keyword(s):  
Case Based Reasoning ◽  
Case Based

Kesehatan merupakan hal yang paling berharga bagi manusia, karena siapa saja rentan mengalami gangguan kesehatan. Anak sangat rentan terhadap kuman penyakit dan kepekaan terhadap gejala suatu penyakit merupakan ketakutan sendiri bagi orang tua. Orang tua merupakan orang awam terhadap dunia kesehatan. Sehingga dalam hal ini di bidang kesehatan lebih membutuhkan seorang pakar yang bisa memudahkan mendiagnosa suatu penyakit lebih cepat agar orang tua dapat melakukan pencegahan lebih awal yang sekiranya bisa membutuhkan waktu lebih lama jika berkonsultasi dengan dokter ahli. Tujuan dari penelitian ini adalah merancang dan sistem pakar untuk diagnosa penyakit anak dengan metode cased-based reasoning dengan algoritma similarity jaccard pada Puskesmas Halmahera Semarang sehingga membantu memberikan informasi tentang diagnosa penyakit anak pada Puskesmas Halmahera Semarang berbasis web.         Perancangan sistem pakar untuk diagnosa penyakit anak dengan metode cased-based reasoning dengan algoritma similarity jaccard pada Puskesmas Halmahera Semarang ini dibuat dengan menggunakan tools seperti PHP, Xampp, Bootstrap.                 Hasil sistem pakar untuk diagnosa penyakit anak dengan metode cased-based reasoning dengan algoritma similarity jaccard pada Puskesmas Halmahera Semarang dapat membantu memberikan informasi tentang diagnosa penyakit anak pada Puskesmas Halmahera Semarang  

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