Mining behavioral sequence constraints for classification
J De Smedt, G Deeva… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Sequence classification deals with the task of finding discriminative and concise sequential
patterns. To this purpose, many techniques have been proposed, which mainly resort to the …
patterns. To this purpose, many techniques have been proposed, which mainly resort to the …
Coversize: A global constraint for frequency-based itemset mining
Constraint Programming is becoming competitive for solving certain data-mining problems
largely due to the development of global constraints. We introduce the CoverSize constraint …
largely due to the development of global constraints. We introduce the CoverSize constraint …
Knowledge-based sequence mining with ASP
We introduce a framework for knowledge-based sequence mining, based on Answer Set
Programming (ASP). We begin by modeling the basic task and refine it in the sequel in …
Programming (ASP). We begin by modeling the basic task and refine it in the sequel in …
Constraint-based sequential pattern mining with decision diagrams
Constraint-based sequential pattern mining aims at identifying frequent patterns on a
sequential database of items while observing constraints defined over the item attributes …
sequential database of items while observing constraints defined over the item attributes …
An efficient algorithm for mining frequent sequence with constraint programming
The main advantage of Constraint Programming (CP) approaches for sequential pattern
mining (SPM) is their modularity, which includes the ability to add new constraints (regular …
mining (SPM) is their modularity, which includes the ability to add new constraints (regular …
NegPSpan: efficient extraction of negative sequential patterns with embedding constraints
T Guyet, R Quiniou - Data Mining and Knowledge Discovery, 2020 - Springer
Sequential pattern mining is concerned with the extraction of frequent or recurrent
behaviors, modeled as subsequences, from a sequence dataset. Such patterns inform about …
behaviors, modeled as subsequences, from a sequence dataset. Such patterns inform about …
Prefix-projection global constraint and top-k approach for sequential pattern mining
Sequential pattern mining (SPM) is an important data mining problem with broad
applications. SPM is a hard problem due to the huge number of intermediate subsequences …
applications. SPM is a hard problem due to the huge number of intermediate subsequences …
Mining time-constrained sequential patterns with constraint programming
Constraint Programming (CP) has proven to be an effective platform for constraint based
sequence mining. Previous work has focused on standard frequent sequence mining, as …
sequence mining. Previous work has focused on standard frequent sequence mining, as …
Design and implementation of bounded-length sequence variables
We present the design and implementation of bounded length sequence (BLS) variables for
a CP solver. The domain of a BLS variable is represented as the combination of a set of …
a CP solver. The domain of a BLS variable is represented as the combination of a set of …
A sat-based approach for mining association rules
Discovering association rules from transaction databases is one of the most studied data
mining task. Many effective techniques have been proposed over the years. All these …
mining task. Many effective techniques have been proposed over the years. All these …