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Found 19 papers, 4 papers with code
Clustering of timed sequences -- Application to the analysis of care pathways
These methods are then applied in clustering algorithms to propose original and sound clustering algorithms for timed sequences.
SWoTTeD: An Extension of Tensor Decomposition to Temporal Phenotyping
Tensor decomposition has recently been gaining attention in the machine learning community for the analysis of individual traces, such as Electronic Health Records (EHR).
A survey on the semantics of sequential patterns with negation
A sequential pattern with negation, or negative sequential pattern, takes the form of a sequential pattern for which the negation symbol may be used in front of some of the pattern's itemsets.
Human Activity Segmentation Challenge @ ECML/PKDD’23
Despite its importance, existing methods demonstrate limited efficacy on real-world multivariate time series data.
Generating robust counterfactual explanations
Counterfactual explanations have become a mainstay of the XAI field.
VCNet: A self-explaining model for realistic counterfactual generation
Our contribution is the generation of counterfactuals that are close to the distribution of the predicted class.
Temporal Disaggregation of the Cumulative Grass Growth
To address this problem, our method applies time series forecasting using climate information and grass growth from previous time steps.
Experimental study of time series forecasting methods for groundwater level prediction
Each time series is made of daily measurements of groundwater levels and two exogenous variables, rainfall and evapotranspiration.
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences
The need to analyze information from streams arises in a variety of applications.
Semantics of negative sequential patterns
In the field of pattern mining, a negative sequential pattern is specified by means of a sequence consisting of events to occur and of other events, called negative events, to be absent.
Day-ahead time series forecasting: application to capacity planning
In the context of capacity planning, forecasting the evolution of informatics servers usage enables companies to better manage their computational resources.
NegPSpan: efficient extraction of negative sequential patterns with embedding constraints
Such patterns inform about which events are frequently observed in sequences, i. e. what does really happen.
Efficiency Analysis of ASP Encodings for Sequential Pattern Mining Tasks
We propose encodings of the classical sequential pattern mining tasks within two representations of embeddings (fill-gaps vs skip-gaps) and for various kinds of patterns: frequent, constrained and condensed.
Mining relevant interval rules
This article extends the method of Garriga et al. for mining relevant rules to numerical attributes by extracting interval-based pattern rules.
Discriminant chronicles mining: Application to care pathways analytics
Pharmaco-epidemiology (PE) is the study of uses and effects of drugs in well defined populations.
Expert Opinion Extraction from a Biomedical Database
In this paper, we tackle the problem of extracting frequent opinions from uncertain databases.
Declarative Sequential Pattern Mining of Care Pathways
Sequential pattern mining algorithms are widely used to explore care pathways database, but they generate a deluge of patterns, mostly redundant or useless.
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification
In this paper, we design a time series classification scheme that builds on the SIFT framework adapted to time series to feed a Bag-of-Words.
Using Answer Set Programming for pattern mining
Serial pattern mining consists in extracting the frequent sequential patterns from a unique sequence of itemsets.
