scholarly journals Business Case Mining and E-R Modeling Optimization

2021 ◽  
Vol 8 (1) ◽  
pp. 53
Author(s):  
Zhaohao Sun ◽  
Paul Pinjik ◽  
Francisca Pambel
Keyword(s):  
Data Science ◽  
Big Data Analytics ◽  
Database Design ◽  
Business Case ◽  
Case Based Reasoning ◽  
Rule Discovery ◽  
Business Rule ◽  
Optimal Method ◽  
Design Data ◽  
Case Based

Business case mining and business rule discovery are at the center for entity relationship (E-R) modeling and database design to obtain E-R models. How to transform business cases through business rules into E-R models is a fundamental issue for database design. This article addresses this issue by exploring business case mining and E-R modeling optimization. Business case mining is business rule discovery from a business case. This article reviews case-based reasoning, explores business case-based reasoning, and presents a unified approach to business case mining for business rule discovery. The approach includes people-centered entity/business rule discovery and function-centered entity/business rule discovery. E-R modeling optimization aims to improve the E-R modeling process to get a better E-R diagram that reflects the business case properly. This article proposes a unified optimal method for E-R modeling. The unified optimal method includes people-centered E-R modeling, function-centered E-R modeling, and hierarchical E-R modeling. The approach proposed in this research will facilitate the research and development of E-R modeling, database design, data science, and big data analytics.

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.

An Object-Oriented Model for Conceptual Ship Design Supporting Case-Based Design

2003 ◽  
Vol 40 (03) ◽  
pp. 158-167
Author(s):  
Ben Delatte ◽  
Alley Butler
Keyword(s):  
Conceptual Design ◽  
Data Storage ◽  
Feasibility Study ◽  
Storage System ◽  
Object Oriented ◽  
Case Based Reasoning ◽  
Design Data ◽  
Design Information ◽  
Object Oriented Database ◽  
Case Based

Design of ships, including warships such as submarines, is normally begun with a feasibility study. The feasibility study provides initial proof of concept and becomes a basis for further efforts. Because time and information for analysis is usually limited, historical design data is typically used to help with the generation of conceptual designs. To support automation of design efforts under these circumstances, adaptation and reuse of earlier designs represents a very useful paradigm. This paper presents a data storage system to store historical design data for subsequent reuse in conceptual design. The database is designed to support case-based reasoning and other similar processes in which recall of past solutions becomes a basis for adaptation to form a new solution. The stored data support conceptual design for a submarine or ship using previous design information. The data involve complex geometric information, and an object oriented database system is presented. The object-oriented database stores complex information in a useful format for recall on a "similar to" basis. This architecture allows case-based reasoning and other recall-based systems to utilize feature-based design information based on similarity to new requirements. To avoid using information that is sensitive and/or classified, this system is demonstrated using unclassified commercial submarine and Maritime Administration ship data. Experiences with two generations of prototype software are discussed, and conclusions about system utility are reached.

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
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