Therefore, conceptual services
that fall within the overlapping cluster regions should be subject to inspection for reusability
and asset-consolidation possibilities. The same overlapping regions should also be inspected for
discovery of new conceptual services because of potential reuse and functionality redundancy
concerns.
Conceptual Service Hierarchical Clusters. The conceptual clustering and machine learning
paradigm12 was coined in the early 1980s. Its main promise was to enable manipulation of concepts
by grouping them in distinctive hierarchical categories and enabling relationships between
cluster members. The outcomes of these studies were a variety of conceptual clustering algorithms.
The most popular and rudimentary method is the COBWEB,13 which was devised by
Tax Benefits
Liquidity
Stability
Diversification
Safety
Diversification, Liquidity, Stability
Safety, Stability
Tax Benefits, Liquidity
1
2
3
Cluster
Cluster
Cluster
EXHIBIT 5.18 CONCEPTUAL OVERLAPPING SERVICE CLUSTERS
Deliverables 109
Loan Verification Cluster
Loan Processing Cluster
Risk Assessment Cluster
Loan Questionnaire Cluster
EXHIBIT 5.19 CONCEPTUAL HIERARCHICAL CLUSTERS EXAMPLE
Douglas H. Fisher in 1987. His approach enables the creation of hierarchical clusters in which
the various tree nodes and their affiliated siblings represent various concepts.
The service conceptualization process acknowledges the benefits of this concept-clustering
mechanism, and its contribution to the conceptual service hierarchical clusters notion.
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