Contigra: Graph Mining with Containment Constraints
In this paper, we develop Contigra for efficient graph mining with containment constraints. We first model the impact of constraints in terms of dependencies across exploration tasks, and then exploit the dependencies to develop: (a) task fusion that merges correlated tasks to increase cache reuse; (b) task promotion that allows explorations to continue from available …
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Theory of Constraints – Mining Differently
Eli Goldratt's TOC is a well-known concept and extremely effective tool in the Order system. Our Productivity Platform tool is typically deployed by experts …
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Constraint-Based Association Rule Mining | Semantic Scholar
This calls for constraint-based association rule mining. The user usually needs to wait for a long period of time to get numerous association rules, out of which only a small fraction may be interesting to the user, and often incurs a high computational cost that is disproportionate to what he wants to get. The problem of association rule ...
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Giving a Voice to your Mining Process
A case study of a major Zambian open pit mine was used to research and establish the constraints of open pit mining in Zambia in meeting productivity targets and to propose strategies to streamline operations to improve overall …
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FP-growth Mining of Frequent Itemsets Constraint-based Mining
Succinctness in Constraint-Based Mining Succinctness : Given A 1, the set of items satisfying a succinct constraint C, then any set S satisfying C is based on A 1, i.e., S contains a subset belonging to A 1 Idea : whether an itemset S satisfies constraint C can be determined based on the singleton items which are in S min(S.Price) ≤v is succinct
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Efficient mining of sequential patterns with time constraints: …
Instead of mining these constraints on the fly during the data sequence analysis, we attempted to use time constraint preprocessing for efficiently identifying generalized frequent sequences. We proposed a new algorithm called G tc based on the fundamental principles of levelwise algorithms but in which time constraints are handled in the ...
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Integration of lean, Six Sigma and theory of constraints for
The Theory of Constraints (TOC) is an area of ongoing development and growth that warrants further investigation (Ikeziri et al., 2018). ... Business managers of the mining industry will be more ...
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Constraint-Based Data Mining
Mining patterns turns to be the so-called inductive query evaluation process for which constraint-based Data Mining techniques have to be designed. An inductive query specifies declara-tively the desired constraints and algorithms are used to compute the patterns satisfying the constraints in the data. We survey important results of this active ...
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Mining constraints in role-based access control
Constraints are an important aspect of role-based access control (RBAC) and sometimes argued to be the principal motivation of RBAC. While role engineering is proposed to define an architectural structure of the organization's security policies, none of the work has employed constraint mining in migrating a non-RBAC system to an RBAC system to our …
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Restrict Mining
Restrict Mining is commonly used to refine/optimize the mining amount of a previous surface in any period, restrict depth to a specific value which the deposit could achieve and extract the best ore in custom advances.
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Surface Constraints
MiningMath uses a surface-constrained mine production scheduling, which is an improvement of the idea proposed by Marinho (2013). Surfaces are one of the most important constraints, allowing the user to …
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A Rough Set Model for Constraint Driven Mining of
suitable for constraint driven mining. They have presented a systematic study of regular expression a constraints imposition and presented various application oriented examples for tough but ...
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gPrune: A Constraint Pushing Framework for Graph Pattern …
Constraint-based frequent pattern mining has been studied in the context of associa-tion rule mining by Ng et al.[9], which identifies three important classes of constraints: monotonicity, antimonotonicity and succinctness and develops efficient constraint-based frequent itemset mining algorithms for a single constraint. Ng et al.also pointed out
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Mining Time-constrained Sequential Patterns with Constraint …
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 well as frequent sequence mining with a maximum 'gap' between two matching events in …
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Constraint-Based Pattern Mining
where θ is a user-defined threshold.. By modifying the pattern language, the data language and the constraints, different data mining problems can be formalized. The main aim of constraint-based pattern mining is to build generic languages in which programmers can express pattern mining problems in terms of constraints, and to develop systems that can process …
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Digital twins and Theory of Constraints (TOC) in …
Discover how the Theory of Constraints (TOC) and digital twins work together to identify and manage production bottlenecks in mining. Learn how always-on constraints models help maximise throughput, improve decision …
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Mining Time-constrained Sequential Patterns with Constraint …
In this section, we revisit the preliminary concepts for both Sequential Pattern Mining (SPM) and Constraint Programming (CP). Most of these concepts can be found for SPM in [1, 41]andin[34] for CP. 2.1 Sequential pattern mining background Assume Lis an alphabet, that is, a list of possible symbols. Table 1a represents an example
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Constraint-based sequential pattern mining: The consideration of
Due to its inefficiency and ineffectiveness, the importance of constraint-based pattern mining has been emphasized [13], [14], [27]. Many approaches have also been proposed to consider the interesting issue of time constraints [8], [25], [33]. Users are allowed to specify their focus in the mining process through various time constraints and ...
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UNIT IV ASSOCIATION RULE MINING AND CLASSIFICATION
Mining Frequent Patterns, Associations and Correlations – Mining Methods – Mining Various Kinds of Association Rules – Correlation Analysis – Constraint Based Association Mining – Classification and Prediction – Basic Concepts – Decision Tree
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Mining top-k frequent patterns in the presence of the memory constraint
We explore in this paper a practicably interesting mining task to retrieve top-k ( closed ) itemsets in the presence of the memory constraint.Specifically, as opposed to most previous works that concentrate on improving the mining efficiency or on reducing the memory size by best effort, we first attempt to specify the available upper memory size that can be …
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Theory of Constraints
The Theory of Constraints (TOC) applies to the mining cycle and its activities for stoping and development. Research was directed towards a study using TOC to identify typical mining cycle constraints within current mining operations while developing a model (or manual) that can be used by mining companies to utilise the theory of constraints, in a consistent and meaningful …
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Theory of Constraints
The Theory of Constraints (TOC) applies to the mining cycle and its activities for stoping and development. Research was directed towards a study using TOC to identify typical mining cycle constraints within current mining operations while developing a model (or manual) that can be …
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Constraint Programming for Mining Borders of Frequent …
based on constraint programming to mine both bor-ders of frequent itemsets. One can easily decide which border to mine by setting a simple parameter. For this, we introduce two new global constraints, FREQUENTSUBS and INFREQUENTSUPERS, with complete polynomial propagators. We then con-sider the problem of mining borders with additional constraints.
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Mining Significant Sequential Contrast Patterns
This section first presents the notation used for contrast pattern mining. Then the anti-monotonic (p)-value constraint will be introduced.This method follows the (p)-value bounding method previously introduced in the context of association rule mining [].Here this bound is rephrased as an anti-monotonic constraint and is adapted for contrast data mining for …
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Mining Negatives Association Rules Using Constraints
In this work we address the problem of mining strong negative rules by extending the SAT-Based approach proposed in [1]. We show that the conviction constraint leads to a non-linear constraints that have to be managed efficiently to prune the search space.
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Application of Mining Width-Constrained Open Pit Mine …
This article presents a novel approach to address the mining width-constrained open pit mine production scheduling problem in the context of medium-term planning. A mathematical formulation is proposed to incorporate mining width constraints into the production scheduling process, aiming to maximize the NPV of the schedule while ensuring enough room …
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Evaluating constraints
It is important to analyze scenarios to measure the impact of each constraint on the project's net present value (NPV), from the Super Best Case to a detailed setup. For …
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17 Constraint-based Data Mining
which hold in the data. Mining patterns turns to be the so-called inductive query evaluation process for which constraint-based Data Mining techniques have to be designed. An induc-tive query specifies declaratively the desired constraints and algorithms are used to compute the patterns satisfying the constraints in the data.
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Constraint-Based Mining of Web Page Associations
types of constraints during the mining process, namely anti-monotone and monotone constraints. We apply our algorithm on web navigational data with constraints to generate fo-cused associations between web page visits. Our contribution are in two areas. First, we provide a constraint-based association rule mining algorithm for the web access log
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A Survey of Mining Association Rules Using Constraints
Constraints based mining enable users to concentrate on mining interested association rules instead of the complete set of association rule."The constraints can be defined as the condition that ...
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