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Using trees to mine multirelational databases

Aída Jiménez, Fernando Berzal, Juan-Carlos Cubero
2011 Data mining and knowledge discovery  
This paper also describes how these frequent tree patterns can be used, for instance, to mine association rules in multirelational databases.  ...  This paper proposes a new approach to mine multirelational databases.  ...  Acknowledgments We would like to thank the anonymous referees for their valuable comments and suggestions, which gave us the chance to improve the quality of this manuscript.  ... 
doi:10.1007/s10618-011-0218-x fatcat:cxkbf2gejjdufhojx2aazjebfq

Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database [chapter]

Willi Klösgen, Michael May
2002 Lecture Notes in Computer Science  
Search strategies of data mining algorithms are efficiently integrated with queries in an object-relational query language and executed in a database to enable scalability for spatial data.  ...  SubgroupMiner is an advanced subgroup mining system supporting multirelational hypotheses, efficient data base integration, discovery of causal subgroup structures, and visualization based interaction  ...  Then, standard data mining methods such as decision trees can be applied.  ... 
doi:10.1007/3-540-45681-3_23 fatcat:3cny5ce3abdyvam3pnqowwbeda

Multirelational classification: a multiple view approach

Hongyu Guo, Herna L. Viktor
2008 Knowledge and Information Systems  
Multirelational classification aims at discovering useful patterns across multiple inter-connected tables (relations) in a relational database.  ...  In addition, the method has practical significance: it is appropriate for directly mining many real-world databases.  ...  Introduction Multirelational Data Mining (MRDM) aims to discover useful patterns across multiple relations (tables) in a relational database.  ... 
doi:10.1007/s10115-008-0127-5 fatcat:35bzua4jejbnzllrgctxzqducy

A Multi-Relational Decision Tree Learning (MRDTL) Approach: A Survey

Patel Rinkal, Rajanikanth Aluvalu
2014 IOSR Journal of Computer Engineering  
Now a day's most of the real world data stored in relational database but the decision tree induction method is used to find knowledge from flat data relations only, but can't discover pattern from relational  ...  Data Mining is the process of extracting useful knowledge from large set of data. There are number of data mining techniques available to find hidden knowledge from huge set of Data.  ...  Multi-relational Data Mining (MRDM) aims to extract useful patterns across multiple tables in a relational database.  ... 
doi:10.9790/0661-16297481 fatcat:mmvekhcpcfc67p7lihc7vnzfeq

State of Art of Multi Relational Data Mining Approaches: A Rule Mining Algorithm

Neelamadhab Padhy, M. Kannan
2013 International Journal of Computer Applications  
database.  ...  In this 21 st century is completely called as the information science where the large organizations need useful knowledge. The data mining algorithms look for patterns in data.  ...  The property can be used to eliminate useless candidate to speed up the mining process.  ... 
doi:10.5120/10719-5485 fatcat:xlptzbubzjer5i4p2o7lhza3uy

Reducing the size of databases for multirelational classification: a subgraph-based approach

Hongyu Guo, Herna L. Viktor, Eric Paquet
2012 Journal of Intelligent Information Systems  
Multirelational classification aims to discover patterns across multiple interlinked tables (relations) in a relational database.  ...  Our method identifies a set of strongly uncorrelated subgraphs from the original database schema, to use for training, and discards all others.  ...  Multirelational data mining algorithms often need to use information from both the five relations and the four join relationships to build a relational model to categorize each tuple from the target relation  ... 
doi:10.1007/s10844-012-0229-0 fatcat:jelbaf6dfrczrmqznb72lilhvm

Analysis and Comparative Study of Classifiers for Relational Data Mining

Vimalkumar B.Vaghela, Kalpesh H. Vandra, Nilesh K. Modi
2012 International Journal of Computer Applications  
To classify data from relational database need of multi-relational classification arise which is used to analyze relational database and used to predict behavior and unknown pattern automatically which  ...  data mining approaches.  ...  Multirelational data mining faces two major challenges. First, it is much more difficult to model multi-relational data.  ... 
doi:10.5120/8765-2685 fatcat:5vxdwr2ng5h6ho32o2x6x7g6mi

A Study on Classification Approaches across Multiple Database Relations

Dr. M. Thangaraj, C.R. Vijayalakshmi
2011 International Journal of Computer Applications  
Lots of algorithms have been proposed to build accurate and scalable classifiers.  ...  Classification is an important task in data mining and machine learning, which has been studied extensively and has a wide range of applications.  ...  Selection graph model can use database language SQL to directly deal with relational tables of database.  ... 
doi:10.5120/1740-2366 fatcat:ianpqmt25vb6bbpmajvc76qxxy

Relational Classification using Multiple View Approach with Voting

Shraddha Modi
2013 International Journal of Computer Applications  
To classify data from relational format need of multirelational classification arise which is used to analyze relational data and used to predict behaviour and unknown pattern automatically.  ...  Classification is an important task in data mining and machine learning, in which a model is generated based on training dataset and that model is used to predict class label of unknown dataset.  ...  Conventional single-table data mining algorithms such as such as Decision Trees, SVMs, or Neural Networks are used in order to learn the target concept from each view of the database separately.  ... 
doi:10.5120/12153-8126 fatcat:njzueaegvnehhowcdyd4fk4qt4

Identifying and Preventing Data Leakage in Multi-relational Classification

Hongyu Guo, Herna L. Viktor, Eric Paquet
2010 2010 IEEE International Conference on Data Mining Workshops  
Abstract-Relational database mining, where data are mined across multiple relations, is increasingly commonplace.  ...  For instance, consider a financial database classification task to determine whether a loan is considered to be high risk.  ...  Also, Guo and Viktor [21] utilized this formula to select a subset of useful views for multirelational classification.  ... 
doi:10.1109/icdmw.2010.33 dblp:conf/icdm/GuoVP10 fatcat:q3e6lsi2urefnlquzkdjbyumim

A Relative Analysis of Multi-Relational Decision Tree Learning Algorithm

2017 International Journal of Science and Research (IJSR)  
We had used some of the real world data sets from multiparous data mining sweepstakes and accomplished a graphical comparison for the forenamed two approaches.  ...  In order to deal with records in relational databases MRDTL broadens TILDE"s [18] approach. First order logic clauses are used to represent decisions (nodes) in the tree.  ...  Hence, the precision of decision trees constructed using MRDTL becomes a major concern as these missing value attribute are pretty common in real multirelational datasets.  ... 
doi:10.21275/art20164150 fatcat:e7mcyharrnayrifcjvz44el6g4

CoMMA: a framework for integrated multimedia mining using multi-relational associations

Ankur M. Teredesai, Muhammad A. Ahmad, Juveria Kanodia, Roger S. Gaborski
2005 Knowledge and Information Systems  
In this paper we also present a multi-relational extension to the FP-Tree algorithm to accomplish the association rule mining task more effectively compared to the currently used de-centralized version  ...  The motivation for using multi-relational association rule mining for multimedia data mining is to exhibit the potential accorded by multiple descriptions for the same image (such as multiple people labeling  ...  We would also like to thank all those people who helped us in getting the data set for this project. We would like to thank Vani Mandava for her editing help.  ... 
doi:10.1007/s10115-005-0221-x fatcat:ro46cu4wt5djjhmnydmgmfs4ga


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  ...  documents in order to perform each of the mining tasks.  ...  XAR-Miner transforms data in the XML document and constructs an Indexed XML Tree (IX-tree) if the XML data can be fully loaded into main memory or Multirelational databases (Multi-DB) otherwise that perfectly  ... 
doi:10.1145/1062745.1062785 dblp:conf/www/ZhangZLW05 fatcat:fl3qx7el5bfdrc5x6vfxsmxfqi

Privacy Disclosure and Preservation in Learning with Multi-Relational Databases

Hongyu Guo, Herna L. Viktor, Eric Paquet
2011 Journal of Computing Science and Engineering  
Abstract There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations.  ...  One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage.  ...  In addition, we wish to thank the anonymous reviewers for their insightful comments on our submission, which helped improve the paper quality.  ... 
doi:10.5626/jcse.2011.5.3.183 fatcat:k5q2rpcvbred5nyxkdvqe6ugbq

Logical Languages for Data Mining [chapter]

Fosca Giannotti, Giuseppe Manco, Jef Wijsen
2004 Logics for Emerging Applications of Databases  
In the field of machine learning, inductive logic programming has broadened its scope toward extending standard data mining tasks from the usual attribute-value setting to a multirelational setting.  ...  At the end, we indicate the potential use of logic for unifying different existing data mining formalisms.  ...  to a multirelational setting, where each example is a (small) relational database.  ... 
doi:10.1007/978-3-642-18690-5_9 fatcat:6s6zu676szbsbjlxyxllv3qtzm
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