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Extension of Business Rule Sets Using Data Mining of GUHA Association Rules

Stanislav Vojír
2015 Conference on Theory and Practice of Information Technologies  
The integration can be realized using full integration, as black box classification model and also using dynamic integration with data mining system.  ...  The following paper is intended to introduce three suitable ways of using data mining of GUHA association rules in conjunction with existing set of business rules.  ...  Acknowledgment This paper was processed with contribution of long term institutional support of research activities and by IGA project 20/2013 by Faculty of Informatics and Statistics, University of Economics  ... 
dblp:conf/itat/Vojir15 fatcat:3v7ceh5sbbb63ja7jvit5p2gkq

The case-based decision support system in the field of IT-consulting

T V Avdeenko, E S Makarova
2017 Journal of Physics, Conference Series  
The method of classification is based on the original algorithm of transformation of cases (precedents) sample to the set of linguistic rules allowing one to make relevant decisions.  ...  Classification of cases in the ontology is executed by means of fuzzy inference.  ...  In [3] , we have obtained encouraging results of improving the efficiency of cases classification by integrating case-based and a rule-based models with the use of fuzzy logic.  ... 
doi:10.1088/1742-6596/803/1/012008 fatcat:gbn7xlls6fckpeiztjblorvr7m

Procedural interference in perceptual classification: Implicit learning or cognitive complexity?

Robert M. Nosofsky, Roger D. Stanton, Safa R. Zaki
2005 Memory & Cognition  
Researchers have argued that an implicit procedural-learning system underlies performance for information integration category structures, whereas a separate explicit system underlies performance for rule-based  ...  By contrast, the magnitude of interference is greatly reduced for an information integration structure that is cognitively simple.  ...  Note that whereas combinations of independent-decision boundaries correspond to explicit rules that can be easily verbalized, such is not the case for information integration structures.  ... 
doi:10.3758/bf03193227 pmid:16532858 fatcat:4m33ciiqb5ay7ehp7f2nqeqjxe

COVCOR20 at WNUT-2020 Task 2: An Attempt to Combine Deep Learning and Expert rules [article]

Ali Hürriyetoğlu and Ali Safaya and Nelleke Oostdijk and Osman Mutlu and Erdem Yörük
2020 arXiv   pre-print
In the scope of WNUT-2020 Task 2, we developed various text classification systems, using deep learning models and one using linguistically informed rules.  ...  These results hardly indicate any progress in line of integrating machine learning and expert rules driven systems.  ...  Acknowledgements We have shown that ML and rule-based ap- proaches yield complementary output for text The authors from Ko University are funded by the classification tasks in various  ... 
arXiv:2009.03191v1 fatcat:fzd6qwouojafnplinak4pxx7fy

Understanding the crucial differences between classification and discovery of association rules

Alex A. Freitas
2000 SIGKDD Explorations  
The goal of this position paper is to contribute to a clear understanding of the profound differences between the association-rule discovery and the classification tasks.  ...  We argue that the classification task can be considered an ill-defined, nondeterministic task, which is unavoidable given the fact that it involves prediction; while the standard association task can be  ...  Integrating Classification and Association Rule Discovery Granted, there has been some work on integrating classification and association rule discovery.  ... 
doi:10.1145/360402.360423 fatcat:mbdy3lx73zhktdvebxeugmfkye

Abduction in Classification Tasks [chapter]

Maurizio Atzori, Paolo Mancarella, Franco Turini
2003 Lecture Notes in Computer Science  
The aim of this paper is to show how abduction can be used in classification tasks when we deal with incomplete data.  ...  Most of these rule-based classifiers make the assumption that at classification time we can know all about new given examples.  ...  Acknowledgments This work has been carried out within the project Clickworld (MIUR S585-P).  ... 
doi:10.1007/978-3-540-39853-0_18 fatcat:nhnka63amvh3xmy26ylgvazm6i

Case-based learning: Beyond classification of feature vectors [chapter]

David W. Aha, Dietrich Wettschereck
1997 Lecture Notes in Computer Science  
We review the recent literature on case-based learning, focusing on alternative performance tasks and more expressive case representations.  ...  . * This is a companion paper for the ECML-97 MLNet Workshop with the same title.  ...  Acknowledgements Thanks to Len Breslow, H~ctor Mufioz-Avila, Jerzy Surma, and Henry Tirri for their comments on an earlier draft of this paper.  ... 
doi:10.1007/3-540-62858-4_96 fatcat:k3lqmqepxfeqlauxuvivbdcli4


Geoffrey I. Webb, Jason Wells, Zijian Zheng
2012 Machine Learning  
They also provided favorable evaluations of both the specific integrated software, a system called The Knowledge Factory, and of the general value of machine learning for knowledge acquisition.  ...  In addition, we found that users expected the expert systems created through the integrated approach to have higher accuracy than those created without machine learning and rated the integrated approach  ...  Acknowledgments This research has been supported by the Australian Research Council and the Apple University Development Fund.  ... 
doi:10.1023/a:1007504102006 fatcat:wbortcuvbvcyzk7xl6scqv32wy

How to detect cognitive strategies: commentary on 'Differentiation and integration: guiding principles for analyzing cognitive change'

Han L.J. van der Maas, Marthe Straatemeier
2008 Developmental Science  
Using 80% in all cases is non-optimal and unnecessary. By using BMA or LCA classification is optimized. Siegler and Chen claim that RAM allows for the discovery of new rules.  ...  Siegler and Chen propose to use differentiation and integration as principles to derive rules or strategies that children use for this task. They come up with five strategies.  ... 
doi:10.1111/j.1467-7687.2008.00690.x pmid:18576952 fatcat:tjvxb7x6tfcrzbsjlllwzy4fau

Supporting start-to-finish development of knowledge bases

Ray Bareiss, Bruce W. Porter, Kenneth S. Murray
1989 Machine Learning  
The task of KI is to interact with the knowledge engineer to integrate this new information.  ...  Using inference rules defined for the retrieved knowledge structures, KI forms the expectation that the embryo in a nonendospermic seed will die of starvation.  ...  the training cases.  ... 
doi:10.1007/bf00130714 fatcat:yoktsjbdxzfhtcgzf2xvskqile

Learning and transfer of category knowledge in an indirect categorization task

Sebastien Helie, F. Gregory Ashby
2011 Psychological Research  
Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm.  ...  Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and viceversa).  ...  If this is the case, the learning in information-integration conditions should be task specific and no transfer should be observed.  ... 
doi:10.1007/s00426-011-0348-1 pmid:21660482 fatcat:rcua5fsrrjeczdyc4nivztbsb4

Your Brain Knows if You're Iron Deficient: Distinct Brain Dynamics in Iron Deficient vs. Sufficient Females in a Visual Category Learning Task

Michael Wenger, Stephanie Rhoten, Lisa De Stefano, Amy Barnett, Laili Boozary
2021 Current Developments in Nutrition  
Both tasks involved classifying gray-scale gabor patches on the basis of spatial frequency and orientation; one task used an easily-verbalized rule (rule-based, RB), the other required complex integration  ...  Results For both tasks, successful classification was possible before 200 ms of processing on the basis of fewer than 12 electrodes.  ...  Both tasks involved classifying gray-scale gabor patches on the basis of spatial frequency and orientation; one task used an easily-verbalized rule (rule-based, RB), the other required complex integration  ... 
doi:10.1093/cdn/nzab049_042 fatcat:3lwp6fem6bgn7pe3vpj2t2fapy

Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex

Michael W. Cole, Joset A. Etzel, Jeffrey M. Zacks, Walter Schneider, Todd S. Braver
2011 Frontiers in Human Neuroscience  
We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks.  ...  Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks.  ...  Computations were performed using the facilities of the Washington University Center for High Performance Computing, which were partially provided through grant NCRR 1S10RR022984-01A1.  ... 
doi:10.3389/fnhum.2011.00142 pmid:22125519 pmcid:PMC3221399 fatcat:2nwwwa54y5ablf4jason265gje

Recursive Learning of Genetic Algorithm Featuring Incremental Attribute Learning for Higher Dimensional Classification Problems

Haofan Zhang, Sheng-Uei Guan, Mengjun Xu
2012 International Journal of Machine Learning and Computing  
Rule-based classifiers trained by Genetic Algorithms (GAs) have been one of the most prevailing solutions for pattern classification problem.  ...  Decomposition and Varied Rule Set (RLGA).  ...  One particular application of GAs is on the training of rule-based classifiers for pattern classification problems, and the most successful attempts on various applications in history are the Pittsburgh  ... 
doi:10.7763/ijmlc.2012.v2.241 fatcat:g3fur44gyrfzfm6noesyqs3jnq

Choking and excelling under pressure in experienced classifiers

Darrell A. Worthy, Arthur B. Markman, W. Todd Maddox
2009 Attention, Perception & Psychophysics  
Pressure caused performance decrements both for experienced classifiers performing rule-based tasks and for those performing information-integration tasks, as compared with control groups.  ...  After extensive training on either a rule-based or an information-integration classification task, half of the participants performed the same task on a fifth day while under pressure to earn a monetary  ...  Scott Lauritzen and all the research assistants in MaddoxLab for their help collecting data, and we thank members of the UT Psychology Motivation Group for useful comments and feedback.  ... 
doi:10.3758/app.71.4.924 pmid:19429969 pmcid:PMC2708085 fatcat:jakominfirgttebdnb6kf7x2ia
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