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Fuzzy sets, uncertainty, and information
Properties of measures of information in evidence and possibility theories
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Problems in formal temporal reasoning
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On probability-possibility transformations
Fuzzy Sets and Systems
Measures of uncertainty in expert systems
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Algorithms on strings, trees, and sequences: computer science and computational biology
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Maintaining knowledge about temporal intervals
Communications of the ACM
ACM Transactions on Computational Logic (TOCL)
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Annals of Mathematics and Artificial Intelligence
A Survey of Temporal Knowledge Discovery Paradigms and Methods
IEEE Transactions on Knowledge and Data Engineering
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Temporal Reasoning over Linear Discrete Time
JELIA '96 Proceedings of the European Workshop on Logics in Artificial Intelligence
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SSDBM '02 Proceedings of the 14th International Conference on Scientific and Statistical Database Management
Algorithms for Guiding Clausal Temporal Resolution
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Fuzzy constraint networks for signal pattern recognition
Artificial Intelligence - Special issue: Fuzzy set and possibility theory-based methods in artificial intelligence
Extracting Uncertain Temporal Relations from Mined Frequent Sequences
TIME '06 Proceedings of the Thirteenth International Symposium on Temporal Representation and Reasoning
International Journal of Intelligent Systems
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Artificial Intelligence in Medicine
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Artificial Intelligence in Medicine
Similarity relations and fuzzy orderings
Information Sciences: an International Journal
A sound and complete fuzzy temporal constraint logic
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Loss and gain functions for CBR retrieval
Information Sciences: an International Journal
An Architecture Proposal for Adaptive Neuropsychological Assessment
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Severity Evaluation Support for Burns Unit Patients Based on Temporal Episodic Knowledge Retrieval
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Combinations of case-based reasoning with other intelligent methods
International Journal of Hybrid Intelligent Systems - CIMA-08
Introducing attribute risk for retrieval in case-based reasoning
Knowledge-Based Systems
Avian influenza: Temporal modeling of a human to human transmission case
Expert Systems with Applications: An International Journal
Length of stay prediction for clinical treatment process using temporal similarity
Expert Systems with Applications: An International Journal
Reprint of "Length of stay prediction for clinical treatment process using temporal similarity"
Expert Systems with Applications: An International Journal
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Similarity is an essential concept in case-based reasoning (CBR). In domains in which time plays a relevant role, CBR systems require good temporal similarity measures to compare cases. Temporal cases are traditionally represented by a set of temporal features, defining time series and temporal event sequences. In the particular situation where these features are not homogeneous (i.e. combination of qualitative and quantitative information), systems find difficulties in performing the CBR cycle. Furthermore, temporal similarity measures cannot directly apply the efficient time series techniques, requiring new approaches to deal with these heterogeneous sequences. To this end, recent proposals are focused on direct matching between pairs of features within sequences, mainly based on classical distances. However, three limitations to the traditional approaches have been identified: (1) they do not consider the implicit temporal relations amongst all features of the sequence (ignoring a large amount of temporal information); (2) they ignore the uncertainty produced in any process of analogy; (3) they are designed to compare pairs of sequences, limiting their use to basic aspects of the Retrieval step of CBR (no benefits on other CBR steps). Temporal constraint networks have proved to be useful tools for temporal representation and reasoning, and can be easily extended to manage imprecision and uncertainty. An approach to solve similarity problems could be the transformation of these heterogeneous sequences into uncertain temporal relations, obtaining a temporal constraint network. The overall uncertainty of this network can be considered as an effective indicator of the sequences similarity. Therefore, this paper proposes a non-classical approach to measure temporal similarity of cases which are heterogeneous temporal event sequences. Given two or more sequences, the temporal similarity is measured by describing a unique temporal scenario of possibilistic temporal relations and calculating the uncertainty produced.