International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Designing a Call Center with Impatient Customers
Manufacturing & Service Operations Management
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
Centralization as a design consideration for the management of call centers
Information and Management
Interpretable Hierarchical Clustering by Constructing an Unsupervised Decision Tree
IEEE Transactions on Knowledge and Data Engineering
Advances in Fuzzy Clustering and its Applications
Advances in Fuzzy Clustering and its Applications
Top 10 algorithms in data mining
Knowledge and Information Systems
Feature Selection for Time Series Forecasting: A Case Study
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Short communication: Data mining based intelligent analysis of threatening e-mail
Knowledge-Based Systems
Classification rule discovery for the aviation incidents resulted in fatality
Knowledge-Based Systems
Cost-sensitive classification with respect to waiting cost
Knowledge-Based Systems
Identifying critical variables of principal components for unsupervised feature selection
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Validity-guided (re)clustering with applications to image segmentation
IEEE Transactions on Fuzzy Systems
Generating an interpretable family of fuzzy partitions from data
IEEE Transactions on Fuzzy Systems
Mathematical and Computer Modelling: An International Journal
An ensemble of decision cluster crotches for classification of high dimensional data
Knowledge-Based Systems
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Nowadays, call centers are common in different areas of activity providing customer services, medical attention, security services, etc. Each type of call center has its own particularities but all call centers have to plan the availability of resources at each time period to support the incoming calls. The emergency call centers are a special case with extra restrictions. In this context, this work is devoted to providing support for the decision making about resource planning of an emergency call center in order to reach its mandatory quality of service. This is carried out by the extraction of interpretable knowledge from the activity data collected by an emergency call center. A linguistic prediction, categorization and description of the days based on the call center activity and information permits the workload for each category of day to be known. This has been generated by a fuzzy version of an unsupervised decision tree (FUDT), merging decision trees and clustering. This involves quality indexes to reach an adequate trade-off between the tree complexity and the category quality in order to guarantee interpretability and performance. This unsupervised approach deals correctly with the real management of this type of centers generating and preserving expert knowledge.