C4.5: programs for machine learning
C4.5: programs for machine learning
Empirical methods for artificial intelligence
Empirical methods for artificial intelligence
Machine Learning
Developing Industrial Case-Based Reasoning Applications: The Inreca Methodology
Developing Industrial Case-Based Reasoning Applications: The Inreca Methodology
simVar: A Similarity-Influenced Question Selection Criterion for e-Sales Dialogs
Artificial Intelligence Review
Machine Learning
A Comparison of Incremental Case-Based Reasoning and Inductive Learning
EWCBR '94 Selected papers from the Second European Workshop on Advances in Case-Based Reasoning
A Dynamic Approach to Reducing Dialog in On-Line Decision Guides
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
A Similarity-Based Approach to Attribute Selection in User-Adaptive Sales Dialogs
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
INRECA: A Seamlessly Integrated System Based on Inductive Inference and Case-Based Reasoning
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Intelligent Sales Support with CBR
Case-Based Reasoning Technology, From Foundations to Applications
minimizing dialog length in interactive case-based reasoning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Increasing dialogue efficiency in case-based reasoning without loss of solution quality
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Product recommendation with interactive query management and twofold similarity
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Case based reasoning and the search for knowledge
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Experience management: foundations, development methodology, and internet-based applications
Experience management: foundations, development methodology, and internet-based applications
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Recent research activities in the field of attribute selection for carrying on dialogs with on-line customers have focused on entropy-based approaches that make use of information gain measures. These measures consider the distribution of attribute values in the case base and are focused on their ability to reduce dialog length. The implicit knowledge contained in the similarity measures is neglected. In previous work, we proposed the similarity-influenced selection method simVar, which selects the attributes that induce the maximum change in similarity distribution amongst the candidate cases, thereby partitioning the case base into similar and dissimilar cases. In this paper we present an evaluation of the selection methods using three domains with distinct characteristics. The comparison of the selection methods is based on the quality of the dialogs generated. Statistical analysis was used to support the evaluation results.