[PDF] Top 20 CMRules: Mining sequential rules common to several sequences
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CMRules: Mining sequential rules common to several sequences
... — Sequential rule mining is an important data mining task with wide ...discovering sequential rules common to several sequences use very restrictive ... Voir le document complet
18
Mining Multi-Dimensional and Multi-Level Sequential Patterns
... Multi-Level Rules The work in [Srikant and Agrawal 1996] introduces the hierarchy management in the ex- traction of association rules and sequential ...possible to extract association ... Voir le document complet
36
Discovery of Unexpected Sequences: from Sequential Patterns to Implication Rules
... order to obtain unexpected terms, and finally unexpected pages and unexpected concepts are extracted by ranking discovered unexpected ...exception rules in the context of association rule mining ... Voir le document complet
201
Hardness of longest common subsequence for sequences with bounded run-lengths
... longest common subsequence (lcs for short) problem is a classic and well-studied problem in computer science with extensive applications in diverse areas ranging from spelling error corrections to molecular ... Voir le document complet
12
Mining association rules for the quality improvement of the production process
... ability to learn and comprehend facts and principles in order to acquire knowledge and apply it in prac- ...refers to both incremental and breakthrough improvement in organizational performance ( ... Voir le document complet
13
Mining a Multimodal Corpus for Non-Verbal Signals Sequences Conveying Attitudes
... chose to use GTrace, successor to FeelTrace (Cowie et ...it to a single dimension to make the annotation task slightly ...how sequences of non-verbal signals are interpreted in terms of ... Voir le document complet
9
Using Function Words for Authorship Attribution: Bag-Of-Words vs. Sequential Rules
... shown to be the most effective attribution method (Diederich et ...due to the fact that SVMs are less sensitive to irrelevant features in terms of degradation in accuracy, and permit one to ... Voir le document complet
10
Using sequential pattern mining to explore learners' behaviors and evaluate their correlation with performance in inquiry-based learning
... closed to our methodology, [ 22 ] suggests an algorithm based on a com- bination of sequence mining techniques to identify differentially frequent pat- terns between two groups of ...] to find ... Voir le document complet
15
Progressive sequential pattern mining: steerable visual exploration of patterns with PPMT
... a mining strategy (from guideline G3) To implement our progressive pattern mining algorithm, we chose to start from the GSP [29] algorithm, available in the SPMF library ...pattern ... Voir le document complet
10
Mining minimal non-redundant association rules using frequent closed itemsets
... iation rules is of primary importan e be ause, in the majority of ases, real-life databases lead to several thousands asso iation rules with high on den e and among whi h are many redundan ... Voir le document complet
16
Assessing the interestingness of temporal rules with Sequential Implication Intensity
... association rules [19], the sequential im- plication intensity SII measures the statistical significance of the rules a −−−→ ...ω To do so, it quantifies the unlikelihood of the smallness of ... Voir le document complet
18
Mining aeronautical data by using visualized driven rules extraction approach
... Data Mining aims at researching relevant information from a huge vol- ume of ...thanks to algorithms, or manual, for instance by using visual exploration ...Data Mining which helps the specialist ... Voir le document complet
13
An improved bound on the least common multiple of polynomial sequences
... Finally, we note that Theorem 1.4 proves Conjecture 1.5 for d = 2. In a couple of different directions, Rudnick and Zehavi [7] have studied the growth of L f along a shifted family of polynomials f a (x) = f 0 (x) − a, ... Voir le document complet
10
Using sequential pattern mining to explore learners' behaviors and evaluate their correlation with performance in inquiry-based learning
... closed to our methodology, [ 22 ] suggests an algorithm based on a com- bination of sequence mining techniques to identify differentially frequent pat- terns between two groups of ...] to find ... Voir le document complet
16
Ethics and observational studies in medical research: various rules in a common framework.
... country to the ...particular, several French observational studies were rejected or retracted by United States peer reviewed journals, because their protocols have not been submitted to an ... Voir le document complet
5
GenMiner: mining non-redundant association rules from integrated gene expression data and annotations
... of rules extracted by GenMiner. Rules 1 and 2 highlight a general reduction of protein synthe- sis, ribosomal organization and cell maintenance following a heat shock, leading to cellular ...damages. ... Voir le document complet
3
Deep phenotyping unstructured data mining in an extensive pediatric database to unravel a common KCNA2 variant in neurodevelopmental syndromes
... able to identify genetically similar patients using a VSM ...used to compute the similarity distance between an index patient and all the patients in the data ...in common. It might help to ... Voir le document complet
5
A virtual reality-based approach for interactive and visual mining of association rules
... is to start from the frequent items, similar to the Appriori ...obtain rules involving these and other items (Figure ...associated rules according to statistical ...arenas to ... Voir le document complet
229
Setting-up rules to characterize microsegregation
... strategy to adopt for chemical analysis will depend on the evolution of the experimental ...consists to choose a regular point grid analysis with a grid step larger than this ...large to allow for a ... Voir le document complet
11
Mining RDF Data of COVID-19 Scientific Literature for Interesting Association Rules
... association rules, also known as association rule mining, is an important data mining ...rule mining has been a thriving field of research, which has contributed many effective techniques for ... Voir le document complet
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