Abstract
Constraint-based pattern discovery is at the core of numerous data mining tasks. Patterns are extracted with respect to a given set of constraints (frequency, closedness, size, etc). In practice, many constraints require threshold values whose choice is often arbitrary. This difficulty is even harder when several thresholds are required and have to be combined. Moreover, patterns barely missing a threshold will not be extracted even if they may be relevant. The paper advocates the introduction of softness into the pattern discovery process. By using Constraint Programming, we propose efficient methods to relax threshold constraints as well as constraints involved in patterns such as the top-k patterns and the skypatterns. We show the relevance and the efficiency of our approach through a case study in chemoinformatics for discovering toxicophores.
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Notes
For the frequency measure, \(max_m = \mid\cal{T}\mid\); for the size measure, \(max_m = \mid\cal{I}\mid\).
The closed constraint is used to reduce pattern redundancy. Indeed, closed skypatterns make up an exact condensed representation of the whole set of skypatterns (Soulet et al. 2011).
Lethal concentration of a substance required to kill half the members of a tested population after a specified test duration.
A fragment denominates a connected part of a chemical structure containing at least one chemical bond.
European Chemicals Bureau http://ecb.jrc.ec.europa.eu/documentation/ now http://echa.europa.eu/.
A chemical Ch contains an item A if Ch supports A, and A is a frequent subgraph of \(\mathcal{T}\).
The rigidity of a subgraph is equal to 2e/v(v − 1), where e (resp. v) is the number of its edges (resp. vertices).
Ratio of the number of solutions containing a toxicophore by the total number of solutions.
Smiles code is a line notation for describing the structure of chemical molecules: http://www.daylight.com/dayhtml/doc/theory/theory.smiles.html.
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Ugarte, W., Boizumault, P., Loudni, S. et al. Soft constraints for pattern mining. J Intell Inf Syst 44, 193–221 (2015). https://doi.org/10.1007/s10844-013-0281-4
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DOI: https://doi.org/10.1007/s10844-013-0281-4