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Modifying Logic of Discovery for Dealing with Domain Knowledge in Data Mining

Jan Rauch
2010 International Conference on Concept Lattices and their Applications  
The goal of the paper is to discuss a possibility to adapt the logic of discovery to data mining.  ...  It is 4f tD = S T AR , U T AR , 4ft-Miner, 4ft-Filter, 4ft-Synt . 4ft-Miner The 4ft-Miner procedure mines for association rules ϕ ≈ ψ, see section 4.  ...  Semantic systems S T AR and U T AR together with the procedures 4ft-Miner, 4ft-Filter, and 4ft-Synt constitute a framework for a process of data mining for association rules based on domain knowledge.  ... 
dblp:conf/cla/Rauch10 fatcat:5acwel2rc5f65a2deoinqh2vb4


Petr Berka
2016 Neural Network World  
LISp-Miner is primarily focused on mining for various types of association rules, but unlike "classical" association rules proposed by Agrawal, LISp-Miner introduces a greater variety of different types  ...  We describe the 4ft-Miner and KEX procedures and show how they can be used to analyze data related to loan applications.  ...  Acknowledgement This paper was prepared with the contribution of long-term institutional support of research activities by the Faculty of Informatics and Statistics, University of Economics, Prague.  ... 
doi:10.14311/nnw.2016.26.029 fatcat:x7gqu3lwbbdafdw7exwvscaviy

Practical Aspects of Data Mining Using LISp-Miner

Petr Berka
2016 Computing and informatics  
We will review the different types of knowledge patterns discovered by the system, and discuss their applicability for various data mining tasks.  ...  The paper describes some practical aspects of using LISp-Miner for data mining. LISp-Miner is a software tool that is under development at the University of Economics, Prague.  ...  Šimůnek, see [13] ) mines for patterns of the form α β : ϕ ≈ ψ/γ (6) A true SD4ft pattern refers to a situation when a 4ft-association rule φ ≈ ψ found for a subset of the analyzed data defined by the  ... 
dblp:journals/cai/Berka16 fatcat:ly4dowr5y5fovkqkcpwlvo54am

Content-based Retrieval of Analytical Reports

Václav Lín, Jan Rauch, Vojtech Svátek
2002 Redirecting ...  
We elaborate the technique for statistical association rules as specific form of discovered knowledge, demonstrate its formal apparatus on examples from the medical domain, and outline the perspectives  ...  Analytic reports are special textual documents containing condensed results from a data mining process.  ...  The research has been supported by the project LN00B107 of the Ministry of Education of the Czech Republic.  ... 
dblp:conf/rml/LinRS02 fatcat:37ybtibqvnbqplwgipmzivf7ca

Applying Domain Knowledge in Association Rules Mining Process – First Experience [chapter]

Jan Rauch, Milan Šimůnek
2011 Lecture Notes in Computer Science  
First experiences with utilization of formalized items of domain knowledge in a process of association rules mining are described.  ...  We use association rules -atomic consequences of items of domain knowledge and suitable deduction rules to filter out uninteresting association rules.  ...  We apply the 4ft-Miner procedure for mining association rules. It deals with Boolean expressions built from attribute-set of value.  ... 
doi:10.1007/978-3-642-21916-0_13 fatcat:neahy7nc2zfeha5yym2i27v6sy

Ontology-Enhanced Association Mining [chapter]

Vojtěch Svátek, Jan Rauch, Martin Ralbovský
2006 Lecture Notes in Computer Science  
The underlying KDD paradigm is association mining tailored to our 4ft-Miner tool. Experience from two different application domains-medicine and sociology-is presented throughout the paper.  ...  We track them through different phases of the KDD process, from data understanding through task setting to mining result interpretation and sharing over the semantic web.  ...  Acknowledgements The research is partially supported by the grant no.201/05/0325 of the Czech Science Foundation, "New methods and tools for knowledge discovery in databases".  ... 
doi:10.1007/11908678_11 fatcat:mdalu2sv2facxftytno27bg6zu

The GUHA method and its meaning for data mining

Petr Hájek, Martin Holeňa, Jan Rauch
2010 Journal of computer and system sciences (Print)  
The reader easily recognizes similarity with the notion of an "associational rule with support and confidence" introduced by Agrawal [1] about 25 years later: his A and S are elementary conjunctions containing  ...  For the system LISp-Miner and similar (implemented) systems generalizing GUHA see Section 2; for GUHA using fuzzy logic see Section 3. For some related computer systems see [27, 65, 112,113].  ...  The procedure 4ft-Miner [83, 97] is the enhanced procedure ASSOC [20, 28] . The 4ft-Miner mines for association rules ϕ ≈ ψ and for conditional association rules ϕ ≈ ψ/γ .  ... 
doi:10.1016/j.jcss.2009.05.004 fatcat:dymascg4y5e2bd7hxj3u2guude

EverMiner - towards Fully Automated KDD Process [chapter]

M. imnek, J. Rauch
2011 New Fundamental Technologies in Data Mining  
For simplicity reasons we would discuss only 4ft-association rule syntax that is used in the 4ft-Miner procedure.  ...  They mine not for associational rules only but for an enhanced version called 4ft-asociational rules (see [Rauch & Šimůnek, 2005a] ) and for other types of patterns -e.g. conditional frequencies, K×L  ...  The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications.  ... 
doi:10.5772/13998 fatcat:3xkiej5cpbgpxgxgguznkkxvbi

Mining Attributes Patterns of Defective Modules for Object Oriented Software

Bharavi Mishra, K. K. Shukla
2012 International Journal of Computer Applications  
For defect pattern mining we used GUHA (General Unary Hypothesis Automaton) procedure which is oldest yet very powerful method of pattern mining.  ...  The basic idea of GUHA procedure is to mine the entire possible and interesting hypothesis supported by the data in predefined logical form.  ...  The basic GUHA procedure 4FT miner used bit string approach for association rule generation. The procedure 4FT miner provides a way for automatic interesting hypothesis generation and verification.  ... 
doi:10.5120/8610-2462 fatcat:5whsp3qhrjcdfmrjm3v2jiubni

Business Rules Mining Using GUHA Method for the Personalization of Commercial Offers

Stanislav Vojir, Zdenek Smutny
2017 Engineering Economics  
This method is based on mining association rules using the GUHA method. The association rules are converted into business rules and then combined with other manually defined business rules.  ...  The practical illustration uses a combination of the data mining system LISp-Miner and the business rule system JBoss Drools, which are freely available tools.  ...  Acknowledgement This work was carried out within the project VSE IGS F4/29/2016 financially supported by the University of Economics, Prague.  ... 
doi:10.5755/ fatcat:ap7yzrrsbfdh5d2vpsvfnsx6l4

Investigating Root Causes of Railway Track Geometry Deterioration – A Data Mining Approach

Mikko Sauni, Heikki Luomala, Pauli Kolisoja, Esko Turunen
2020 Frontiers in Built Environment  
For this purpose, a new method was explored. After reviewing methodologies, the chosen approach was an association rule data mining method: General Unary Hypotheses Automaton (GUHA).  ...  Therefore, the GUHA method was found to be a suitable method for investigating the root causes of track geometry deterioration from comprehensive railway track structure data.  ...  This research was funded by the Finnish Transport Infrastructure Agency (Väylä) and the Tampere University Foundation sr.  ... 
doi:10.3389/fbuil.2020.00122 fatcat:ixfopcoswjbibpscabm6c5ijwm

Relational Data Mining and GUHA

Tomás Karban
2005 Databases, Texts, Specifications, Objects  
This paper presents an extension of GUHA method for relational data mining of association rules.  ...  This paper shows heuristic approach for GUHA method to deal with it, as well as other methods helping with the relational data mining experience.  ...  For example, GUHA procedure 4ft-Miner mines for association rules from a single table, while other GUHA procedures (see [4, 7, 8] ) mine for other types of patterns.  ... 
dblp:conf/dateso/Karban05 fatcat:yurn47t6wracdlcxbfbrp2n6zq

Semantic Analytical Reports: A Framework for Post-processing Data Mining Results [chapter]

Tomáš Kliegr, Martin Ralbovský, Vojtěch Svátek, Milan Šimůnek, Vojtěch Jirkovský, Jan Nemrava, Jan Zemánek
2009 Lecture Notes in Computer Science  
The framework input is constituted by PMML and description of background knowledge. Using the Topic Maps standard, a Data Mining Association Rule Mining ontologies are introduced.  ...  Prototype implementation of the framework for association rules was implemented and is demonstrated on the PKDD'99 Financial Data set.  ...  GUHA Method The GUHA method is realized by GUHA procedures, such as 4FT procedure for mining association rules.  ... 
doi:10.1007/978-3-642-04125-9_12 fatcat:u2xpkwscfzggxefdawqu7hrqwe

Transforming Association Rules to Business Rules: EasyMiner meets Drools

Stanislav Vojír, Tomás Kliegr, Andrej Hazucha, Radek Skrabal, Milan Simunek
2013 International Web Rule Symposium  
EasyMiner ( is a web-based association rule mining software based on the LISp-Miner system.  ...  This paper presents a proof-of-concept workflow for learning business rules with EasyMiner from transactional data.  ...  Acknowledgements The work described here was supported by grant IGA 20/2013 of the University of Economics, Prague and by the LinkedTV EU FP7 project.  ... 
dblp:conf/ruleml/VojirKHSS13 fatcat:pinxfga3jfbyfill4mrywpsl6i

LISp-Miner Control Language description of scripting language implementation

Milan Simunek
2014 Journal of Systems Integration  
This paper introduces the LISp-Miner Control Languagea scripting language for the LISp-Miner system, an academic system for knowledge discovery in databases.  ...  In this sense, the language is a necessary prerequisite for the EverMiner project of data mining automation.  ...  There are several types of patterns the LISp-Miner could mine for: 4ft-association ruleswe would like to stress that we do not mine for simple association rules derived from shopping baskets in the sense  ... 
doi:10.20470/jsi.v5i2.193 fatcat:knqjmookkffcvljgrdtlvdcsoi
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