Data Cleaning Model for XML Datasets using Conditional Dependencies

Hakawati, Mohammed Ragheb; Yacob, Yasmin Mohd; Raof, Rafikha Aliana A.; Jabiry, Mustafa M.Khalifa; Alhudiani, Eiad Syaf

doi:10.24018/ejece.2020.4.1.163

Cited by 3 publications

(7 citation statements)

References 13 publications

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“…These enhanced dependencies are XIND hold only on a subset of the XML document, which satisfies the condition rather than the entire document, also, to be checked only using the related dependency, not both [11]. Another case for XFD, as known, XFD can check the consistency by at least two paths, if there exists a single path contains a wrong value, then, how can an inconsistency in a text node be captured?…”

Section: A Motivational Examplementioning

confidence: 99%

“…Traditional XML Dependencies (XFD, XIND, XAFD) have limit capability toward cleaning the XML tree effectively. However, recently, a conditional version of these dependencies presented to overcome their limitation and to open a new era of cleaning approaches for XML cleaning [11], [12]. Sections below cover the basics of these conditional dependencies.…”

Section: Literature Reviewmentioning

confidence: 99%

“…XML Conditional Inclusion Dependencies (XCIND) syntax [11] is too close to strong path notations [18], as this notation is the closest notation to the relational notation and the most explicit description of XML Inclusion Dependencies.…”

Section: ) Xml Conditional Inclusion Dependenciesmentioning

confidence: 99%

“…Moreover, any attribute of R P (repeatable path) cannot participate in both types of paths (Conditional and Field). However, in this article, we will omit the Mining XIND phase and considered a set of traditional XIND dependency is already available, refer to [11] to see the full XCIND mining algorithm.…”

Section: Discovering Xcind Pattern Tableausmentioning

confidence: 99%

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Discovering XML Conditional Dependencies for Data Quality Issues

Hakawati

Yacob

Amir

et al. 2020

EJECE

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Extensible Markup Language (XML) is emerging as the primary standard for representing and exchanging data, with more than 60% of the total; XML considered the most dominant document type over the web; nevertheless, their quality is not as expected. XML integrity constraint especially XFD plays an important role in keeping the XML dataset as consistent as possible, but their ability to solve data quality issues is still intangible. The main reason is that old-fashioned data dependencies were basically introduced to maintain the consistency of the schema rather than that of the data. The purpose of this study is to introduce a method for discovering pattern tableaus for XML conditional dependencies to be used for enhancing XML document consistency as a part of data quality improvement phases. The notations of the conditional dependencies as new rules are designed mainly for improving data instance and extended traditional XML dependencies by enforcing pattern tableaus of semantically related constants. Subsequent to this, a set of minimal approximate conditional dependencies (XCFD, XCIND) is discovered and learned from the XML tree using a set of mining algorithms. The discovered patterns can be used as a Master data in order to detect inconsistencies that don’t respect the majority of the dataset.

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Section: A Motivational Examplementioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: ) Xml Conditional Inclusion Dependenciesmentioning

confidence: 99%

Section: Discovering Xcind Pattern Tableausmentioning

confidence: 99%

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Discovering XML Conditional Dependencies for Data Quality Issues

Hakawati

Yacob

Amir

et al. 2020

EJECE

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“…Moreover, one of the formats used for data representation and transaction in the World Wide Web is XML format [4]. Thus, they hold an enormous percentage (58%) in the web [18]. Besides, event happens in business process is captured in XML format as well.…”

Section: Introductionmentioning

confidence: 99%

Framework to Mine XML Format Event Logs

Ang¹,

Jamil²,

Shaharanee³

2022

ijasca

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A lot of applications including event logs and web pages uses XML format for utilizing, keeping, transferring and displaying data. Thus, volume of data expressed in XML has increase rapidly. Numerous research has been done to extract and mine information from XML documents. Mining XML documents allows an understanding to the architecture and composition of XML documents. Generally, frequent subtree mining is one of the methods to mine XML documents. Frequent subtree mining searches the relation between data in a tree structured database. Due to the architecture and the composition of XML format, normal data mining and statistical analysis difficult to be performed. This paper suggests a framework that flattens and converts tree structured data into structured data, while maintaining the information of architecture and the composition of XML format. To gain more information from event logs, converting into structured data from semistructured format grants more ability to perform variety data mining techniques and statistical test. Keywords: Flatten Sequential Structure Model, XML Format Event Logs, Data Mining, Statistical Analysis.

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A Framework to Analyze Business Process Log in XML Format

et.al¹

2021

TURCOMAT

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XML has numerous uses in a wide variety of web pages and applications. Some common uses of XML include tasks for web publishing, web searching and automation, and general application such as for utilize, store, transfer and display business process log data. The amount of information expressed in XML has gone up rapidly. Many works have been done on sensible approaches to address issues related to the handling and review of XML documents. Mining XML documents offera way to understand both the structure and the content of XML documents. A common approach capable of analysing XML documents is frequent subtree mining.Frequent subtree mining is one of the data mining techniques that finds the relationship between transactions in a tree structured database. Due to the structure and the content of XML format, traditional data mining and statistical analysis hardly applied to get accurate result. This paper proposes a framework that can flatten a tree structured data into a flat and structured data, while preserving their structure and content.Enabling these XML documents into relational structured data allows a range of data mining techniques and statistical test can be applied and conducted to extract more information from the business process log.

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Data Cleaning Model for XML Datasets using Conditional Dependencies

Cited by 3 publications

References 13 publications

Discovering XML Conditional Dependencies for Data Quality Issues

Discovering XML Conditional Dependencies for Data Quality Issues

Framework to Mine XML Format Event Logs

A Framework to Analyze Business Process Log in XML Format

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