Using Attribute Oriented Induction High Level Emerging Pattern (AOI-HEP) to Mine Frequent Patterns

Abstract

<p><span lang="EN-US">Frequent patterns in Attribute Oriented Induction High level Emerging Pattern (AOI-HEP), are recognized when have maximum subsumption target (superset) into contrasting (subset) datasets (contrasting </span><span lang="EN-US">⊂</span><span lang="EN-US"> target) and having large High Emerging Pattern (HEP) growth rate and support in target dataset. HEP Frequent patterns had been successful mined with AOI-HEP upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS with the number of instances of 48842, 569, 2458285 and 256932 respectively and each dataset has concept hierarchies built from its five chosen attributes. There are 2 and 1 finding frequent patterns from adult and breast cancer datasets, while there is no frequent pattern from census and IPUMS datasets. The finding HEP frequent patterns from adult dataset are adult which have government workclass with an intermediate education (80.53%) and America as native country(33%). Meanwhile, the only 1 HEP frequent pattern from breast cancer dataset is breast cancer which have clump thickness type of AboutAverClump with cell size of VeryLargeSize(3.56%). Finding HEP frequent patterns with AOI-HEP are influenced by learning on high level concept in one of chosen attribute and extended experiment upon adult dataset where learn on marital-status attribute showed that there is no finding frequent pattern.</span></p>

Analysis of IDS Alerts by Generalizing Features and Discovering Emerging Patterns

“…Then, the aggregation operation is performed on the duplicate records, and the output of the concepts is generated. The database is then divided into two different attack and normal classes, and according to the method provided in Warnars (2016), frequent patterns and similar patterns are found between the two classes. Then, the output of this method is given to the unit of discovery of emerging patterns, and according to a specific threshold value, emerging patterns are discovered.…”

“…After generalising the relationships, the database is divided into two parts, the attack database and the normal database. According to Warnars (2016), the generalised relationships between the two databases are compared and categorised into different classes. Then, by implementing the emerging patterns algorithm on these classes, various trends have been extracted, from which knowledge can be obtained in the form of different rules.…”

“…Queries with SQL structure were created with the aim of data mining query language (DMQL) (Elfeky et al, 2000). Attribute-oriented induction has been used in extracting rules (Cheung et al, 2000), classification (Cai et al, 1990), clustering (Wu and Xie, 2003), and in discovering repetitive patterns (Warnars, 2016). Another interesting technique used in this article is emerging patterns.…”

Mining specific and representative information by the attribute‐oriented induction method

“…AOI technologies were also integrated with different application areas. For example, AOI can be used in traditional Chinese medicine prescriptions (Liu et al, 2007), discovering general knowledge of spatial databases (Lu, Han, & Ooi, 1993), enhancing classification results (Junior & Nicoletti, 2017), strategy making for Internet service provider management (Li, Shue, & Lee, 2008), and industry machines predictive maintenance (Fernandez-Anakabe, Uriguen, & Ortega, 2019), visualizing massive network traffic flows (Jiang et al, 2018), discovering outpatient clinic knowledge from databases (Tsumoto, 2000), mining frequent patterns (Warnars, 2016) or association rules (Warnars, Lumban, Heryadim, Trisetyarso, & Sanchez, 2018), and discovering infrequent patterns in smart healthcare environments (Ahmed & Barkat Ullah, 2018).…”

Object oriented metrics to measure the quality of software upon PHP source code with PHP_depend study case request online system application

“…Request online system is a web based application which is built with Personal Home Page (PHP) language programming in order to record and control all improvement or update request in SAP application. For future implementation, the intelligent of this application will be extended with such as technology such as Data Warehouse [19,20,21,22,23] or Data Mining with some options algorithms such as Attribute Oriented Induction(AOI) [24,25,26,27,28,29,30,31] or Attribute Oriented Induction High level Emerging Patterns (AOI-HEP) [32,33,34,35,36].…”