Weighted fuzzy similarity relations in case-based reasoning: A case study in classification

Effort models and effort estimates help project managers allocate resources, control costs and schedule, and improve current practices, leading to projects that are finished on time and within budget. In the context of Web development and maintenance, these issues are also crucial, and very challenging, given that Web projects have short schedules and a highly fluidic scope. Therefore, the objective of this chapter is to introduce the concepts related to Web effort estimation and effort estimation techniques. In addition, this chapter also details and compares, by means of a case study, three effort estimation techniques, chosen for this chapter because they have been to date the ones mostly used for Web effort estimation: Multivariate regression, Case-based reasoning, and Classification and Regression Trees. The case study uses data on industrial Web projects from Spanish Web companies.

Download Full-text

Research on case retention strategy for industrial case-based reasoning (CBR) system: A practical case study

2012 International Conference on Computer Science and Information Processing (CSIP) ◽

10.1109/csip.2012.6308872 ◽

2012 ◽

Author(s):

Ping Zhou ◽

Wei-Da Yin ◽

Jin-Hui Zhao

Keyword(s):

Case Based Reasoning ◽

Practical Case ◽

Retention Strategy ◽

System A ◽

Case Based

Download Full-text

Improved similarity measure in case-based reasoning: a case study of construction cost estimation

Engineering Construction & Architectural Management ◽

10.1108/ecam-01-2019-0035 ◽

2019 ◽

Vol 27 (2) ◽

pp. 561-578 ◽

Cited By ~ 1

Author(s):

Won-Gil Hyung ◽

Sangyong Kim ◽

Jung-Kyu Jo

Keyword(s):

Cost Estimation ◽

Hybrid Approach ◽

Optimal Solution ◽

Case Based Reasoning ◽

Optimization Approach ◽

Cost Information ◽

Planning Stage ◽

Content Type ◽

Case Based

Purpose Applied a hybrid approach using genetic algorithms (GAs) for a case-based retrieval process in order to increase the overall improved cost accuracy for a case-based library. The paper aims to discuss this issue. Design/methodology/approach A weight optimization approach using case-based reasoning (CBR) with proposed GAs for developing the CBR model. GAs are used to investigate optimized weight generation with an application to real project cases. Findings The proposed CBR model can reduce errors consistently, and be potentially useful in the early financial planning stage. The authors suggest the developed CBR model can provide decision-makers with accurate cost information for assessing and comparing multiple alternatives in order to obtain the optimal solution while controlling cost. Originality/value The system can operate with more accuracy or less cost, and CBR can be used to better understand the effects of factor interaction and variation during the developed system’s process.

Download Full-text

Web Effort Estimation Using Case-Based Reasoning

Cost Estimation Techniques for Web Projects ◽

10.4018/978-1-59904-135-3.ch006 ◽

2008 ◽

pp. 158-202

Author(s):

Emilia Mendes

Keyword(s):

Prediction Accuracy ◽

Early Stage ◽

Real Data ◽

Project Managers ◽

Case Based Reasoning ◽

Effort Estimation ◽

Software Projects ◽

Software Practitioners ◽

Case Based

Software practitioners recognise the importance of realistic effort estimates to the successful management of software projects, the Web being no exception. Having realistic estimates at an early stage in a project’s life cycle allow project managers and development organisations to manage resources effectively. Several techniques have been proposed to date to help organisations estimate effort for new projects. One of these is a machine-learning technique called case-based reasoning. This chapter presents a case study that details step by step, using real data from completed industrial Web projects, how to obtain effort estimates using case-based reasoning, and how to assess the prediction accuracy of this technique. The reason to describe the use of case-based reasoning for effort estimation is motivated by its previous use with promising results in Web effort estimation studies.

Download Full-text