Communications of the ACM - Special issue on parallelism
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
C4.5: programs for machine learning
C4.5: programs for machine learning
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Artificial Intelligence Review - Special issue on lazy learning
Knowledge intensive exception spaces
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Structures for Range Searching
ACM Computing Surveys (CSUR)
Communications of the ACM
Multidimensional binary search trees used for associative searching
Communications of the ACM
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
Dynamically Creating Indices for Two Million Cases: A Real World Problem
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
The Utility Problem Analysed: A Case-Based Reasoning Perspective
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
Efficient Similarity Determination and Case Construction Techniques for Case-Based Reasoning
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Towards Dynamic Maintenance of Retrieval Knowledge in CBR
Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference
Using introspective reasoning to refine indexing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Engineering Applications of Artificial Intelligence
Adaptive case-based reasoning using retention and forgetting strategies
Knowledge-Based Systems
Intelligent system applications in electronic tourism
Expert Systems with Applications: An International Journal
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In this paper, we present an indexing technique for case-based reasoning called D-HS^E, that is shown to be more competent than and twice as efficient as the commonly used R-tree. D-HS^E was designed to addresses periodical competency shortcomings of the related D-HS^M index but unfortunately in doing so some efficiency was seen to be sacrificed. In order to address this problem of competency verses efficiency, we propose an intelligent selection algorithm that automatically analyses the case-base and decides which index (D-HS^M or D-HS^E) should be used to optimize performance. The algorithm is designed to favour competency at the expense of efficiency where a competency gain is deemed highly likely to be achieved by using the less efficient approach. In effect we are proposing a flexible indexing scheme that is aware of changes within its environment and which reacts to these changes to optimize performance.