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Mining Interesting Patterns in Multi-relational Data with N-ary Relationships
[chapter]
2013
Lecture Notes in Computer Science
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Mining patterns from multi-relational data is a problem attracting increasing interest within the data mining community. ...
In this paper we introduce a novel approach to mining patterns in multi-relational data. We propose a new syntax for multi-relational patterns as complete connected subsets of database entities. ...
Acknowledgements We are grateful to Michael Mampaey for providing the Smurfig code and data and for his support in using Smurfig, Siegfried Nijssen for his assistance in using Farmer and Thomas Gärtner ...
doi:10.1007/978-3-642-40897-7_15
fatcat:2sdvgwjbnfgypmyp5tfnkygcwy
Multi-source Data Mining for e-Learning
[article]
2020
arXiv
pre-print
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This challenge is the main focus of our work where we propose to mine multi-source data in order to extract interesting frequent patterns. ...
Pattern mining mining involves extracting interesting frequent patterns from data. ...
Such kind of data is called multi-source data. When there are relations between the sources or between the data dimensions, the data is called multi-relational [5] . ...
arXiv:2009.08791v1
fatcat:nyxcbki4vbcdfg544wtdahr3sy
Multi-Relational Data Mining 2005
2005
SIGKDD Explorations
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A consequence of this is that most data mining tools are based on machine learning algorithms that work on data in attribute-value format. ...
One way to enlarge the expressiveness is to generalize, as in ILP, from onetable mining to multiple table mining, i.e., to support mining on full relational databases. ...
The purpose of multi-relational data mining will be to discover interesting sets of objects in a relational database. ...
doi:10.1145/1117454.1117471
fatcat:m3fmh2g3tnd2hafzazoaeywaxy
Multi-relational data mining
2003
SIGKDD Explorations
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The major types of multi-relational patterns extend the types of propositional patterns considered in single table data mining. ...
When we are looking for patterns in multi-relational data, it is natural that the patterns involve multiple relations. ...
doi:10.1145/959242.959256
fatcat:qbmompgkqfelzcplzuexqbvdvm
Mining Multi-Dimensional Intra and Inter-Association Patterns of Call Records for Targeted Advertising using Multi-Granulation Rough Sets
2019
Informatica (Ljubljana, Tiskana izd.)
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This work presents a multi granulation rough sets model to address the issue of prospect discovery from interest traits depicted in call records. ...
The proposed method solves problems like higher computational complexity and large statistically insignificant patterns space inherent in traditional intra and interpattern mining methods. ...
Bhaskar Sinha for his support in writing this paper. ...
doi:10.31449/inf.v43i3.2161
fatcat:rhc7wip5kvgedjxvqzquuhldn4
Multi-relational data mining 2004
2004
SIGKDD Explorations
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The goal of the workshop was to bring together researchers and practitioners of Data Mining interested in methods and applications of finding patterns in expressive languages from multi-relational, complex ...
In this report we briefly review the 4th Workshop on Multi-Relational Data Mining (MRDM-2005), which was organized by the authors and held in Chicago, IL, on August 21, as part of the workshop program ...
MRDM-2005 was the fourth edition of this Workshop on Multi-Relational Data Mining. Typical data mining approaches look for patterns in a single relation of a database. ...
doi:10.1145/1046456.1046481
fatcat:u363hoo33vdyrhdaqpoqqbpj5e
A Multi-Relational Decision Tree Learning (MRDTL) Approach: A Survey
2014
IOSR Journal of Computer Engineering
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So to extract multi-relational pattern from relational tables we use MRDTL approach. In real world Missing value problem are common in many data mining application. ...
This paper provides survey of multi-relational decision tree learning algorithm to discover hidden multi-relational pattern from relational data sets and also includes some simple technique to deal with ...
Multi-relational data mining framework is based on the search for interesting patterns in the relational database, where multi-relational patterns can be viewed as "pieces of substructure occurred in the ...
doi:10.9790/0661-16297481
fatcat:mmvekhcpcfc67p7lihc7vnzfeq
Handling Item Similarity in Behavioral Patterns through General Pattern Mining
2020
2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
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We introduce G SPM, a behavioral pattern mining algorithm that takes advantage of multi-source data to handle the problem of data similarity. ...
Modeling human behavior on the Web is often performed by sequential pattern mining (SPM). However, the similarity between data elements often results in the decrease of the number of patterns mined. ...
RELATED WORK
A. Sequential Pattern Mining Pattern mining consists of discovering interesting, useful, and unexpected patterns in large databases [7] . ...
doi:10.1109/wiiat50758.2020.00092
fatcat:6f4cdfl6rrd4rg2fpx5h3jqiu4
MR-Radix: a multi-relational data mining algorithm
2012
Human-Centric Computing and Information Sciences
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Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding ...
Conclusion: The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory ...
Competing interests The authors declare that they have no competing interests. ...
doi:10.1186/2192-1962-2-4
fatcat:yycrjkhftbhsbhh7ul5mkkcele
An efficient strategy for mining exceptions in multi-databases
2004
Information Sciences
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While many interstate organizations have an imperative need to analyze their data in multi-databases distributed throughout their branches, traditional multi-database mining utilizes the strategies for ...
mono-database mining: pooling all the data from relevant databases into a single dataset for discovery. ...
Related work Data mining techniques (see [1, 12] ) have been successfully used in many diverse applications. ...
doi:10.1016/j.ins.2003.10.008
fatcat:5li3oeg6jfdtlmkngox7gcmh4q
XAR-miner
2005
Special interest tracks and posters of the 14th international conference on World Wide Web - WWW '05
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In XAR-Miner, raw data in the XML document are first preprocessed to transform to either an Indexed Content Tree (IX-tree) or Multi-relational databases (Multi-DB), depending on the size of XML document ...
and memory constraint of the system, for efficient data selection and AR mining. ...
Association Rule (AR) mining is frequently used to reveal interesting trends, patterns, and rules in large datasets. ...
doi:10.1145/1062745.1062785
dblp:conf/www/ZhangZLW05
fatcat:fl3qx7el5bfdrc5x6vfxsmxfqi
Multi-relational Decision Tree Induction
[chapter]
1999
Lecture Notes in Computer Science
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In this paper we present a framework that allows the efficient discovery of multi-relational decision trees through the exploitation of the domain knowledge encoded in the data model of the database. ...
By going from the standard single-relation approach to the multi-relational approach as in ILP this disadvantage is removed. ...
As was explained in [8, 9] , we view multi-relational data mining as the search for interesting multi-relational patterns. ...
doi:10.1007/978-3-540-48247-5_46
fatcat:tsb2tzq3mbaa5acegpbv7jtk3m
Constraint-Based Pattern Mining in Multi-relational Databases
2011
2011 IEEE 11th International Conference on Data Mining Workshops
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We propose a new framework for constraint-based pattern mining in multi-relational databases. ...
networks in constraint programming; (3) it maps multi-relational pattern mining tasks into constraint programs. ...
This work was supported by a Postdoc and project "Principles of Patternset Mining" from the Research Foundation-Flanders, as well as a grant from the Agency for Innovation by Science and Technology in ...
doi:10.1109/icdmw.2011.54
dblp:conf/icdm/NijssenJG11
fatcat:o2ck6hry5re5vk2lb34aef2cwm
Mining Least Relational Patterns from Multi Relational Tables
[chapter]
2005
Lecture Notes in Computer Science
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Existing mining association rules in relational tables only focus on discovering the relationship among large data items in a database. ...
Results from the implementation reveal that the algorithm is capable of mining rare item in multi relational tables. 2005 , where t.ID is tuple t's ID. ...
the rare data in a single table instead of multi relational tables. ...
doi:10.1007/11527503_9
fatcat:a62flasjk5g23iw7psmly5xvlq
Efficient Classification Rules for Complex Data in Decision Making
2020
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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This paper proposed an efficient classification rules generation mechanism for complex data association and information mining using Multi-Features Patterns Combination (MFPC) method. ...
Information mining in enterprise applications facing challenges due to the complex data distribution in large heterogeneous sources. ...
This paper aim to enhance the methods for multi relational data mining approaches through a multi-features patterns combining approach for mining complex knowledge in complex data for various decision ...
doi:10.35940/ijitee.e2822.039520
fatcat:mtpytotd6vdchib2u6eo7crase
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