scholarly journals Monotonicity and Noise-Tolerance in Case-Based Reasoning with Abstract Argumentation

2021 ◽  
Author(s):  
Guilherme Paulino-Passos ◽  
Francesca Toni
Keyword(s):  
Case Based Reasoning ◽  
Noise Tolerance ◽  
Trade Secrets ◽  
Abstract Argumentation ◽  
Reasoning System ◽  
Legal Domain ◽  
Formal Properties ◽  
The U.S ◽  
Case Based

Recently, abstract argumentation-based models of case-based reasoning (AA-CBR in short) have been proposed, originally inspired by the legal domain, but also applicable as classifiers in different scenarios. However, the formal properties of AA-CBR as a reasoning system remain largely unexplored. In this paper, we focus on analysing the non-monotonicity properties of a regular version of AA-CBR (that we call AA-CBR_>). Specifically, we prove that AA-CBR_> is not cautiously monotonic, a property frequently considered desirable in the literature. We then define a variation of AA-CBR_> which is cautiously monotonic. Further, we prove that such variation is equivalent to using AA-CBR_> with a restricted casebase consisting of all "surprising" and "sufficient" cases in the original casebase. As a by-product, we prove that this variation of AA-CBR_> is cumulative, rationally monotonic, and empowers a principled treatment of noise in "incoherent" casebases. Finally, we illustrate AA-CBR and cautious monotonicity questions on a case study on the U.S. Trade Secrets domain, a legal casebase.

scholarly journals The Determination of the Action towards the Patient’s Psychological Therapy in the Post-accident Using Case-based Reasoning

2018 ◽  
Vol 12 (1) ◽  
pp. 11
Author(s):  
Sri Mulyana ◽  
Ilham Sahputra
Keyword(s):  
Psychological Treatment ◽  
Psychological Therapy ◽  
Case Based Reasoning ◽  
Reasoning System ◽  
Serious Injury ◽  
Accuracy Rates ◽  
Degree Of Similarity ◽  
Case Based

The accident that occurred to somebody will give much suffering; moreover, if the accident gives the serious injury, such as a broken bone which needs to get more seriously treatment. Not only does the patient need the action towards his/her injury, but also he/she needs the psychological therapy in facing the problems happened which is suggested by a psychologist. One of the reasoning method in expert systems is Case-Based Reasoning (CBR). In Case-Based Reasoning, a case-based consists of various cases in conditions or symptoms and solution (the psychological therapy) given. To find out the solution from a new problem given, the system will find any cases in the case-based which have higher the degree of similarity between the cases. This research develops a case-based reasoning system to decide the action of the psychological therapy towards the patients in the post-accident who needs seriously treatment. The psychological therapy involves in giving assistance, consultation, psychiatrist support, and the compound of various actions as well. A case study was conducted from the medical records of psychological treatment at ‘Dr Soeharso’ hospital in Surakarta. Based on the result of the research developed, the action of psychological therapy upon the patient has successfully determined. They have accuracy rates of 60% in the threshold 50% compared to the treatments resulted from the psychologist. The result was found by calculating the degree of similarity between the new issue and all cases existing in the case base.

scholarly journals An Innovative Method for Project Transaction Mode Design Based on Case-Based Reasoning: A Chinese Case Study

2018 ◽  
Vol 10 (11) ◽  
pp. 4127 ◽  
Author(s):  
Jiyong Ding ◽  
Jianyao Jia ◽  
Chenhao Jin ◽  
Na Wang
Keyword(s):  
Continuous Variable ◽  
Project Performance ◽  
Case Based Reasoning ◽  
Scoring Method ◽  
Reasoning System ◽  
Innovative Method ◽  
Performance Predictions ◽  
Construction Experience ◽  
Case Based

Aiming at the design of a project transaction mode, the case-based reasoning (CBR) method is used as a methodology to build a case-based reasoning system based on project performance predictions. Thirty-four cases are initially selected for the practical application. Based on the classical CBR, the performance forecast is added, an improved continuous variable interpolation scoring method is proposed, and three types of manual revision methods are proposed: owner’s preference for the project transaction mode, extreme value, and secondary learning. The innovative method is verified with Nanjing HF Project as an example, and the results show that the case-based reasoning system can optimize the selection and design of the project transaction mode, providing a certain guarantee for project performance and facilitating the transfer of construction experience and knowledge within the construction industry.

scholarly journals Using extended siamese networks to provide decision support in aquaculture operations

2021 ◽  
Author(s):  
Bjørn Magnus Mathisen ◽  
Kerstin Bach ◽  
Agnar Aamodt
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Similar Case ◽  
Decision Makers ◽  
Similarity Function ◽  
Case Based Reasoning ◽  
Similarity Learning ◽  
Reasoning System ◽  
Siamese Networks ◽  
Case Based

AbstractAquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely operate than are traditional sites. To help the industry deal with these challenges, we have developed a decision support system to support decision makers in establishing better plans and make decisions that facilitate operating these sites in an optimal manner. We propose a case-based reasoning system called aquaculture case-based reasoning (AQCBR), which is able to predict the success of an aquaculture operation at a specific site, based on previously applied and recorded cases. In particular, AQCBR is trained to learn a similarity function between recorded operational situations/cases and use the most similar case to provide explanation-by-example information for its predictions. The novelty of AQCBR is that it uses extended Siamese neural networks to learn the similarity between cases. Our extensive experimental evaluation shows that extended Siamese neural networks outperform state-of-the-art methods for similarity learning in this task, demonstrating the effectiveness and the feasibility of our approach.

A Case Based Reasoning System For Recommendation Of Restaurant In Jimbaran Using K-Nearest Neighbor

2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
I Gede Teguh Mahardika ◽  
I Wayan Supriana
Keyword(s):  
Recommendation System ◽  
Nearest Neighbor ◽  
Case Based Reasoning ◽  
Retrieval Process ◽  
K Nearest Neighbor ◽  
Reasoning System ◽  
Human Ability ◽  
And Function ◽  
Case Based ◽  
Selection Of

Culinary is one of the favorite businesses today. The number of considerations to choose a restaurant or place to visit becomes one of the factors that is difficult to determine the restaurant or place to eat. To get the desired place to eat advice, one needs a recommendation system. Decisions made by the recommendation system can be used as a reference to determine the choice of restaurants. One method that can be used to build a recommendation system is Case Based Reasoning. The Case Based Reasoning (CBR) method mimics human ability to solve a problem or cases. The retrieval process is the most important stage, because at this stage the search for a solution for a new case is carried out. The study used the K-Nearest Neighbor method to find closeness between new cases and case bases. With the selection of features used as domains in the system, the results of recommendations presented can be more suggestive and accurate. The system successfully provides complex recommendations based on the type and type of food entered by the user. Based on blackbox testing, the system has features that can be used and function properly according to the purpose of creating the system.

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