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Mining Interesting Patterns in Multi-relational Data with N-ary Relationships [chapter]

Eirini Spyropoulou, Tijl De Bie, Mario Boley
2013 Lecture Notes in Computer Science  
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]

Julie Bu Daher, Armelle Brun, Anne Boyer
2020 arXiv   pre-print
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

Hendrik Blockeel, Sašo Džeroski
2005 SIGKDD Explorations  
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

Sašo Džeroski, Luc De Raedt
2003 SIGKDD Explorations  
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

Jigyasa Bisaria, Kamal Raj Pardasani
2019 Informatica (Ljubljana, Tiskana izd.)  
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

Sašo Džeroski, Hendrik Blockeel
2004 SIGKDD Explorations  
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

Patel Rinkal, Rajanikanth Aluvalu
2014 IOSR Journal of Computer Engineering  
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

Julie Bu Daher, Armelle Brun
2020 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)  
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

Carlos R Valencio, Fernando T Oyama, Paulo Scarpelini, Angelo C Colombini, Adriano M Cansian, Rogeria C G de Souza, Pedro L P Correa
2012 Human-Centric Computing and Information Sciences  
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

Shichao Zhang, Chengqi Zhang, Jeffrey Xu Yu
2004 Information Sciences  
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

Sheng Zhang, Ji Zhang, Han Liu, Wei Wang
2005 Special interest tracks and posters of the 14th international conference on World Wide Web - WWW '05  
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]

Arno J. Knobbe, Arno Siebes, Daniël van der Wallen
1999 Lecture Notes in Computer Science  
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

Siegfried Nijssen, Aida Jimenez, Tias Guns
2011 2011 IEEE 11th International Conference on Data Mining Workshops  
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]

Siti Hairulnita Selamat, Mustafa Mat Deris, Rabiei Mamat, Zuriana Abu Bakar
2005 Lecture Notes in Computer Science  
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  
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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