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Maintaining Evidential Frequent Itemsets in Case of Data Deletion [chapter]

Mohamed Anis Bach Tobji, Boutheina Ben Yaghlane
2010 Communications in Computer and Information Science  
Incremental Maintenance of Frequent Itemsets (IMFI) consists in maintaining a set of extracted patterns when mined data are updated. This field knew considerable improvement in the last decade.  ...  In this work, we maintain incrementally the set of initially extracted itemsets both in cases of insertion and deletion of evidential data. Experimentations led on our method show satisfying results.  ...  This method is less costly in term of execution time. The field of Incremental Maintenance of Frequent Itemsets (IMFI) has attracted attention of several researches.  ... 
doi:10.1007/978-3-642-14055-6_23 fatcat:qiutbgmc7jh3dardwqrgaopgme

Dynamic index selection in data warehouses

Stephane Azefack, Kamel Aouiche, Jerome Darmont
2007 2007 Innovations in Information Technologies (IIT)  
The main advantage of this approach is that it helps update the set of selected indexes when workload evolves instead of recreating it from scratch.  ...  In this paper, we present an automatic, dynamic index selection method for data warehouses that is based on incremental frequent itemset mining from a given query workload.  ...  They reuse the frequent itemsets discovered before transaction database update to compute new frequent itemsets. Updating the set of frequent itemsets is very costly, though.  ... 
doi:10.1109/iit.2007.4430394 fatcat:rhepubhyrjg75mkpwr65muhvxq

Towards An Incremental Maintenance of Cyclic Association Rules

Eya Ben Ahmed, Mohamed Salah Gouider
2010 International Journal of Database Management Systems  
In this paper, we propose an incremental algorithm for cyclic association rules maintenance. The carried out experiments of our proposal stress on its efficiency and performance.  ...  Recently, the cyclic association rules have been introduced in order to discover rules from items characterized by their regular variation over time.  ...  The binary sequence representing the itemset AD is 000010 so sup(AD)=1 <MinFPC=2 < MinSup=4 then AD is called non frequent cyclic itemset denoted NFC.  ... 
doi:10.5121/ijdms.2010.2405 fatcat:au2safvryrdureexum36djfa7m

Incremental Data Mining Using Concurrent Online Refresh of Materialized Data Mining Views [chapter]

Mikołaj Morzy, Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzewicz
2005 Lecture Notes in Computer Science  
We present the framework for the integration of data warehouse refresh process with the maintenance of materialized data mining views.  ...  Users issue series of similar data mining queries, in each consecutive run slightly modifying either the definition of the mined dataset, or the parameters of the mining algorithm.  ...  An itemset with the support higher than minsup is called a frequent itemset. Given a collection of frequent itemsets L.  ... 
doi:10.1007/11546849_29 fatcat:i72raoykcjac5o2yibc2k4oy4i

Towards an incremental maintenance of cyclic association rules [article]

Eya ben Ahmed, Mohamed Salah Gouider
2010 arXiv   pre-print
In this paper, we propose an incremental algorithm for cyclic association rules maintenance. The carried out experiments of our proposal stress on its efficiency and performance.  ...  Recently, the cyclic association rules have been introduced in order to discover rules from items characterized by their regular variation over time.  ...  The binary sequence representing the itemset AB is 011100 so sup(AB)=M inSup=2 then AB is called Frequent Cyclic itemset F C.  ... 
arXiv:1009.5149v1 fatcat:zc2muzulvrgxllyz57a5ebulie

http://www.jcomputers.us/vol11/jcp1102-06.pdf

Mohammad Karim Sohrabi, Vahid Ghods
2016 Journal of Computers  
In this paper, we present a new efficient method to conduct selecting proper set of views to materialization using a frequent itemset mining approach.  ...  The constraint of storage memory on one hand, and the maintenance cost of materialized views when the source data are updated on the other hand, cause that it is impossible to materialize all or even large  ...  Algorithm In this section, we represent the algorithm of our Materialized Views selection based on Frequent Itemset mining (MVFI) and describe its operation.  ... 
doi:10.17706/jcp.11.2.140-148 fatcat:4sc727akrfcirh6jhcpclz3nxi

Analysis of Sequential Mining Algorithms

Surbhi Chandhok, Romil Anand, Soumay Gupta, Aatif Jamshed
2017 International Journal of Computer Applications  
The discovery of Association relationship seeks more attention in data mining due to the constantly increasing amount of data stored in the real application system.  ...  Mining for association rules has its usage in several areas of business such as the process of decision making and the development of customized marketing programs & strategies.  ...  of which the large itemsets are representative Sequence step: Now, from all the sequential database that is transformed, this step produces frequent sequential patterns and forms.  ... 
doi:10.5120/ijca2017914085 fatcat:euevx2giqbc53h5rjpaalb4j3q

A Wind Turbine Fault Detection Approach Based on Cluster Analysis and Frequent Pattern Mining

2014 KSII Transactions on Internet and Information Systems  
In this paper, we propose a fault detection approach which combines cluster analysis and frequent pattern mining to accurately reflect the deteriorating condition of a wind turbine and to indicate the  ...  To aid operators prior to the maintenance process, a condition monitoring system should be able to accurately reflect the actual state of the wind turbine and its major components in order to execute specific  ...  Generation of Rules from Frequent Patterns After all the itemsets which represent frequent patterns from turbine operation data have been found, we generate strong association rules from them.  ... 
doi:10.3837/tiis.2014.02.020 fatcat:vzjq54h6vnhglagzokahymwjsa

DEMON: mining and monitoring evolving data

V. Ganti, J. Gehrke, R. Ramakrishnan
2001 IEEE Transactions on Knowledge and Data Engineering  
Taking this new degree of freedom into account, we describe efficient model maintenance algorithms for frequent itemsets and clusters.  ...  We introduce a new dimension, called the data span dimension, which allows user-defined selections of a temporal subset of the database.  ...  The detection phase relies on the maintenance of the negative border along with the set of frequent itemsets.  ... 
doi:10.1109/69.908980 fatcat:zgiakan64zd37hihi3pjmfoxgq

APIEvolutionMiner: Keeping API evolution under control

Andre Hora, Anne Etien, Nicolas Anquetil, Stephane Ducasse, Marco Tulio Valente
2014 2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE)  
This requires changes to be consistently applied to reflect the new API and avoid further maintenance problems.  ...  In real-world migrations, many methods in the newer version are not present in the old version (e.g., 60% of the methods in Eclipse 2.0 were not in version 1.0).  ...  relevant-assoc-rules(evidences[], min-supp, min-conf) { transactions = select-changes(evidences); frequent-itemsets = find-frequent-itemsets(transactions, min-supp); relevant-itemsets = select the itemsets  ... 
doi:10.1109/csmr-wcre.2014.6747209 dblp:conf/csmr/HoraEADV14 fatcat:xs224y2ezbagzbwk6ajlfshcmi

A Decremental Algorithm for Maintaining Frequent Itemsets in Dynamic Databases [chapter]

Shichao Zhang, Xindong Wu, Jilian Zhang, Chengqi Zhang
2005 Lecture Notes in Computer Science  
Data mining and machine learning must confront the problem of pattern maintenance because data updating is a fundamental operation in data management.  ...  Most existing data-mining algorithms assume that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new data.  ...  with size |DB|; db: the deleted dataset from DB with size |db|; L: the set of frequent itemsets in DB; S 0 : the minimum support specified by the user; Output: L " : the set of frequent itemsets in DB-db  ... 
doi:10.1007/11546849_30 fatcat:bjf5dlzzebemnpggxzywhvmvyq

Concurrent Edge Prevision and Rear Edge Pruning Approach for Frequent Closed Itemset Mining

Anurag Choubey, Dr. Ravindra, Dr. J.L.
2011 International Journal of Advanced Computer Science and Applications  
Past observations have shown that a frequent item set mining algorithm are purported to mine the closed ones because the finish provides a compact and a whole progress set and higher potency.  ...  Anyhow, the newest closed item set mining algorithms works with candidate maintenance combined with check paradigm that is pricey in runtime yet as space usage when support threshold is a smaller amount  ...  Finding a way to mine frequent closed sequences without the help of candidate maintenance seems to be difficult.  ... 
doi:10.14569/ijacsa.2011.021111 fatcat:47p43znhp5hajgijojxkbehatm

DARM: Decremental Association Rules Mining

Mohamed Taha, Tarek F. Gharib, Hamed Nassar
2011 Journal of Intelligent Learning Systems and Applications  
Although many techniques were proposed for maintenance of the discovered rules when new transactions are added, little work is done for maintaining the discovered rules when some transactions are deleted  ...  Frequent item sets mining plays an important role in association rules mining. A variety of algorithms for finding frequent item sets in very large transaction databases have been developed.  ...  ., [19] addressed the maintenance of the frequent patterns space of both incremental and decremental updates.  ... 
doi:10.4236/jilsa.2011.33019 fatcat:2w3n7e2f3vgnfhctsyfli6fdme

Data Dependence Analysis for Defects Data of Relay Protection Devices based on Apriori Algorithm

Mingwei Tian, Lie Zhang, Peng Guo, Hanfang Zhang, Qian Chen, Yanfei Li, Ancheng Xue
2020 IEEE Access  
Step 5: When C3 is generated by L2, Apriori pruning is used: all subsets of frequent itemset must be frequent.  ...  The basic implementation of the method is to discover the frequent itemset according to the combination of all different items and then gives out the ARs.  ...  interest is the reliability analysis and application of artificial intelligence in relay protection system. LIE ZHANG was born in  ... 
doi:10.1109/access.2020.3006345 fatcat:usxsewj5pfdpnhdku76elubxj4

An Experiment to Design an Operation and Maintenance System Integrating Apriori Association Rules for a Telecom Platform

Chengfan Li, Lan Liu, Junjuan Zhao, Yuejun Liu, Simone Morosi
2021 Wireless Communications and Mobile Computing  
In this paper, the Apriori algorithm is firstly used to analyse the fault correlation of the operation and maintenance system of the telecommunications platform to get the alarm message.  ...  Then, the fault risk of the operation and maintenance platform is evaluated intelligently by the system-business alarm causality model.  ...  If the support degree of itemset A is not less than the preset minimum support threshold (min_sup), namely, SðAÞ ≥ min sup, the itemset A is called the frequent itemset and the frequent itemset containing  ... 
doi:10.1155/2021/1185584 fatcat:ubhtskrdyvd3febrznw4j55b24
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