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Association Rule Mining for Multiple Tables With Fuzzy Taxonomic Structures

Praveen Arora, R. K. Chauhan, Ashwani Kush
<span title="">2010</span> <i title="IACSIT Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/473y5rd3tfgnvnlxddqa5aqeoa" style="color: black;">Journal of clean energy technologies</a> </i> &nbsp;
The study focuses on the issue of mining association rules in databases having multiple levels containing fuzzy data with taxonomy and tables to be designed using Entity-Relationship (ER) Models.  ...  Most of the existing data mining algorithms handle databases consisting of single table to find association rules an large databases.  ...  With extended Apriori algorithm, which finds fuzzy association rules helps to discover the related higher level due to the strong association rules.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7763/ijcte.2010.v2.253">doi:10.7763/ijcte.2010.v2.253</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/geotrbji4bbe7dzyvk3dajisxi">fatcat:geotrbji4bbe7dzyvk3dajisxi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720175224/http://www.ijcte.org/papers/253-G639.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/06/0e/060eacc4c7b85659a6dc9e9964ab749098b442fd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7763/ijcte.2010.v2.253"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Fuzzy Ontology based Approach for Flexible Association Rules Mining

Alsayed M., Ahmed M., Mohamed H.
<span title="">2017</span> <i title="The Science and Information Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2yzw5hsmlfa6bkafwsibbudu64" style="color: black;">International Journal of Advanced Computer Science and Applications</a> </i> &nbsp;
The association rules approach is one of the used methods for analyzing, discovering and extracting knowledge and mining the relationships among raw data.  ...  Consequently, generating fuzzy association rules based on fuzzy ontology makes it more human-like and reliable compared with other previous ones.  ...  The Extended SSDM considers the association rule or the fuzzy item to be generalised if the association rule contains all subitems of an ancestor.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14569/ijacsa.2017.080541">doi:10.14569/ijacsa.2017.080541</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pmam3qysknhsrlvj5mdrvmjrum">fatcat:pmam3qysknhsrlvj5mdrvmjrum</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719061648/http://thesai.org/Downloads/Volume8No5/Paper_41-Fuzzy_Ontology_based_Approach_for_Flexible.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e8/e6/e8e64af21b3eccbac9338fed4e14451596f53365.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14569/ijacsa.2017.080541"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Frequent Itemsets from Multiple Datasets with Fuzzy data

Praveen Arora, R. K. Chauhan, Ashwani Kush
<span title="">2011</span> <i title="IACSIT Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/473y5rd3tfgnvnlxddqa5aqeoa" style="color: black;">Journal of clean energy technologies</a> </i> &nbsp;
The study aims to incorporate the previous developed algorithms on mining fuzzy generalized association rules and Mining Association rules in Entity relationship Models to discover a new algorithm.  ...  An example given in the study demonstrates that the proposed mining algorithm can derive multi level fuzzy association rules from multiple datasets in a simple and effective manner.  ...  Crisp Association Rules Mining algorithms can mine only binary attributes that can potentially introduce loss of information due to the sharp ranges where as Fuzzy association rules use fuzzy logic to  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7763/ijcte.2011.v3.313">doi:10.7763/ijcte.2011.v3.313</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/omzx2jbirjde3exyaljic2vsqe">fatcat:omzx2jbirjde3exyaljic2vsqe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810083406/http://www.ijcte.org/papers/313-G798.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c6/ab/c6ab02c63bb856d6ca2f1023a8204fd998e3c224.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7763/ijcte.2011.v3.313"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Mining fuzzy coherent rules from quantitative transactions without minimum support threshold

Chun-Hao Chen, Ai-Fang Li, Yeong-Chyi Lee, Tzung-Pei Hong
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/udakit3l65dttaf22bvkqynv7a" style="color: black;">2012 IEEE International Conference on Fuzzy Systems</a> </i> &nbsp;
Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from the give quantitative transactions.  ...  In this paper, we thus proposed an algorithm for mining fuzzy coherent rules to overcome those problems with the properties of propositional logic.  ...  ACKNOWLEDGMENT This research was supported by the National Science Council of the Republic of China under contract NSC 100-2221-E-032 -065 -.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/fuzz-ieee.2012.6251309">doi:10.1109/fuzz-ieee.2012.6251309</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/fuzzIEEE/ChenLLH12.html">dblp:conf/fuzzIEEE/ChenLLH12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bnadoodx6na5heh7w4o56vjbou">fatcat:bnadoodx6na5heh7w4o56vjbou</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829030033/http://tkuir.lib.tku.edu.tw:8080/dspace/retrieve/78065/Mining+Fuzzy+Coherent+Rules+from+Quantitative.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/aa/d6/aad6e2f5aca57c12b2625437b7a9bd339fccebe1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/fuzz-ieee.2012.6251309"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A Survey of Fuzzy Based Association Rule Mining to Find CoOccurrence Relationships

Anubha Sharma, Asst. Prof. Nirupama Tiwari
<span title="">2014</span> <i title="IOSR Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vabuspdninc75epczdurccts4u" style="color: black;">IOSR Journal of Computer Engineering</a> </i> &nbsp;
The techniques are categorized based upon different approaches. This paper provides the major advancement in the approaches for association rule mining using fuzzy algorithms.  ...  A fuzzy association rule mining (firstly expressed as quantitative association rule mining) has been proposed using fuzzy sets such that quantitative and categorical attributes can be handled.  ...  in which they extend the problem of classification using Fuzzy Association Rule Mining and propose the concept of Fuzzy Weighted Associative Classifier(FWAC).Classification based on Association rules is  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/0661-16158387">doi:10.9790/0661-16158387</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/c2gzdb24y5crzkbh43kpsdilfy">fatcat:c2gzdb24y5crzkbh43kpsdilfy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602091544/http://www.iosrjournals.org/iosr-jce/papers/Vol16-issue1/Version-5/M016158387.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/71/47/7147191c2694d8767bbfa4fd971dd4522ebb3555.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/0661-16158387"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

A multi-level ant-colony mining algorithm for membership functions

Tzung-Pei Hong, Ya-Fang Tung, Shyue-Liang Wang, Yu-Lung Wu, Min-Thai Wu
<span title="">2012</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ozlq63ehnjeqxf6cuxxn27cqra" style="color: black;">Information Sciences</a> </i> &nbsp;
In the past, we proposed a mining algorithm to find suitable membership functions for fuzzy association rules based on ant colony systems.  ...  The final membership functions in the last level are then outputted to the rule-mining phase to find fuzzy association rules.  ...  As for fuzzy data mining, Hong et al. integrated the fuzzy-set concepts and the apriori mining algorithm to obtain fuzzy association rules [13] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ins.2010.12.019">doi:10.1016/j.ins.2010.12.019</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jzr5y3scyzg3zhb2n6tlw44wdu">fatcat:jzr5y3scyzg3zhb2n6tlw44wdu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170815220312/http://isiarticles.com/bundles/Article/pre/pdf/7755.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/95/52/95524f6c70da0648ae00bb8835a7d4c7d481567e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.ins.2010.12.019"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Discovery of Fuzzy Hierarchical Association Rules

Reena Kumari, Jyoti Vashishtha
<span title="2014-07-18">2014</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
Most of the algorithms in data mining find association rules among transactions using binary values and at single concept level.  ...  However it will be more exciting to discover hierarchical association rules for decision makers. In this work we have integrated association rule mining with fuzzy set theory and hierarchy.  ...  The proposed fuzzy mining algorithm can thus generate large itemsets level by level and then derive fuzzy association rules from transaction dataset.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/17292-7762">doi:10.5120/17292-7762</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ixt4xzpqpnhwhkhdl7ac4iav2e">fatcat:ixt4xzpqpnhwhkhdl7ac4iav2e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170706145239/http://research.ijcaonline.org/volume98/number19/pxc3897762.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d8/b1/d8b179ad812754b0f20b82056705fedd9fa47aa2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/17292-7762"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

A new proposal Classification method based on Fuzzy Association Rule Mining for Student Academic Performance Prediction

Giap Cu
<span title="2017-07-01">2017</span> <i title="Vietnam National University Journal of Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lipqyqocanhxzcysu36sh27hgm" style="color: black;">VNU Journal of Science Policy and Management Studies</a> </i> &nbsp;
Theprediction approaching fuzzy association rules (FAR) give advantages in this circumstancebecause it gives the clear data-driven rules for prediction outcome.  ...  Indeed, a modification tree structure of a FP-growth tree is used in fuzzyfrequent itemset mining, when a new requirement rises, the proposed algorithm mines directly inthe tree structure for the best  ...  Background and relate works Fuzzy association rule Fuzzy association rule is extended from crisp association rule by extending the membership function.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.25073/2588-1116/vnupam.4104">doi:10.25073/2588-1116/vnupam.4104</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4cj3d3he6ff6pibsj4x2fqbrre">fatcat:4cj3d3he6ff6pibsj4x2fqbrre</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722214258/https://js.vnu.edu.vn/PaM/article/download/4104/3797" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/15/36/1536cd8e9e7ddebcb13eddffd3fcdc253b317d1f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.25073/2588-1116/vnupam.4104"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Evolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm [chapter]

Stephen G. Matthews, Mario A. Gongora, Adrian A. Hopgood
<span title="">2011</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The novelty of this research lies in exploring the composition of quantitative and temporal fuzzy association rules and the approach of using a hybridisation of a multi-objective evolutionary algorithm  ...  A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented.  ...  Acknowledgements Supported by an Engineering and Physical Sciences Research Council Doctoral Training Account.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-21219-2_26">doi:10.1007/978-3-642-21219-2_26</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mfq4st2o3vamnn453nigwamhum">fatcat:mfq4st2o3vamnn453nigwamhum</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722002553/http://www.adrianhopgood.com/pub/hais2011.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/88/b3/88b3b656cd7404316f348f49eafcac15c7986288.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-21219-2_26"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

An improved approach to find membership functions and multiple minimum supports in fuzzy data mining

Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng
<span title="">2009</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ekjwtd7zwfeipf5aknu4733lzy" style="color: black;">Expert systems with applications</a> </i> &nbsp;
The final best minimum supports and membership functions in all the populations are then gathered together to be used for mining fuzzy association rules.  ...  association rules.  ...  Chan and Au proposed an F-APACS algorithm to mine fuzzy association rules (Chan & Au, 1997) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.eswa.2009.01.067">doi:10.1016/j.eswa.2009.01.067</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iu2ywpoizjhvhghtzxgy34duny">fatcat:iu2ywpoizjhvhghtzxgy34duny</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829195741/http://isiarticles.com/bundles/Article/pre/pdf/22162.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d4/84/d48444185160355dea1b69dfbaeab5826acd500f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.eswa.2009.01.067"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

A Survey on Fuzzy Association Rule Mining Methodologies

Aritra Roy
<span title="">2013</span> <i title="IOSR Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vabuspdninc75epczdurccts4u" style="color: black;">IOSR Journal of Computer Engineering</a> </i> &nbsp;
In this paper, we have studied several well-known methodologies and algorithms for fuzzy association rule mining.  ...  Today there is a huge number of different types of fuzzy association rule mining algorithms are present in research works and day by day these algorithms are getting better.  ...  And this requires domain specific knowledge. Association rule mining is basically of two types. One is classical or crisp association rule mining and the other one is fuzzy association rule mining.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/0661-1560108">doi:10.9790/0661-1560108</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zyt3iqrvtvg3tnkgeenvpyvqdq">fatcat:zyt3iqrvtvg3tnkgeenvpyvqdq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170814001937/http://iosrjournals.org/iosr-jce/papers/Vol15-issue6/A01560108.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2d/a9/2da92c8062a3d77cff80b3264e42c4a7f0a3a8f3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/0661-1560108"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

A fuzzy coherent rule mining algorithm

Chun-Hao Chen, Ai-Fang Li, Yeong-Chyi Lee
<span title="">2013</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/spnlkxfb7fevrarnlb7rv32roy" style="color: black;">Applied Soft Computing</a> </i> &nbsp;
Many fuzzy data mining approaches have thus been proposed for finding fuzzy association rules with the predefined minimum support from the give quantitative transactions.  ...  In this paper, an algorithm for mining fuzzy coherent rules is proposed for overcoming those problems with the properties of propositional logic.  ...  Acknowledgment This research was supported by the National Science Council of the Republic of China under contract NSC 100-2221-E-032-065.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.asoc.2012.12.031">doi:10.1016/j.asoc.2012.12.031</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jgwijhumzbbx5cpxgdxqvolmly">fatcat:jgwijhumzbbx5cpxgdxqvolmly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829060934/http://novintarjome.com/wp-content/uploads/2015/01/A-fuzzy-coherent-rule-mining-algorithm1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/98/ad/98adb267c84a3231bcc11d7a61c31bf04a230767.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.asoc.2012.12.031"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

A Systematic Assessment of Numerical Association Rule Mining Methods

Minakshi Kaushik, Rahul Sharma, Sijo Arakkal Peious, Mahtab Shahin, Sadok Ben Yahia, Dirk Draheim
<span title="2021-06-22">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yzo2wjv2bbh2zo3zo5p7scalee" style="color: black;">SN Computer Science</a> </i> &nbsp;
To deal with the variety of data attributes, the classical association rule mining technique was extended to numerical association rule mining.  ...  In this article, we present a systematic assessment of various numerical association rule mining methods and we provide a meta-study of thirty numerical association rule mining algorithms.  ...  -Papers extending the existing algorithm in numerical association rule mining or quantitative association rule mining.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s42979-021-00725-2">doi:10.1007/s42979-021-00725-2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yhtda5qukrgf3hwmso6w4sh5fe">fatcat:yhtda5qukrgf3hwmso6w4sh5fe</a> </span>
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SPACS: Students' Performance Analysis and Counseling System using Fuzzy logic and Association Rule Mining

Ritu Banswal, Vishu Madaan
<span title="2016-01-15">2016</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
Hence, association rule mining technique helps to generate the accurate results and also decreases the complexity of the system.  ...  General Terms Data mining, Expert System, quality education, academic performance, and fuzzy rule based expert system.  ...  Apriori algorithm is the most significant and efficient algorithm to mine the association rules.  ... 
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Cluster-based Membership Function Acquisition Approaches for Mining Fuzzy Temporal Association Rules

Chun-Hao Chen, Hsiang Chou, Tzung-Pei Hong, Yusuke Nojima
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
mechanism for a fuzzy temporal association rule mining algorithm.  ...  Therefore, fuzzy temporal association rule mining algorithms have also been proposed in the literature.  ...  PROPOSED MINING FRAMEWORK AND ALGORITHMS In this section, the proposed mining framework, which contains two main phases for fuzzy temporal fuzzy association rule mining, is stated in Section III.A.  ... 
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