Case-Based Reasoning for Autonomous Service Failure Diagnosis and Remediation in Software Systems

2006 ◽  
pp. 489-503 ◽  
Author(s):  
Stefania Montani ◽  
Cosimo Anglano
Keyword(s):  
Service Failure ◽  
Failure Diagnosis ◽  
Software Systems ◽  
Case Based Reasoning ◽  
Autonomous Service ◽  
Case Based

Rationalism with a dose of empiricism: combining goal reasoning and case-based reasoning for self-adaptive software systems

2015 ◽  
Vol 20 (3) ◽  
pp. 233-252 ◽  
Author(s):  
Wenyi Qian ◽  
Xin Peng ◽  
Bihuan Chen ◽  
John Mylopoulos ◽  
Huanhuan Wang ◽  
...  
Keyword(s):  
Software Systems ◽  
Case Based Reasoning ◽  
Adaptive Software ◽  
Goal Reasoning ◽  
Case Based ◽  
Self Adaptive

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.

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