A Framework to Analyze Business Process Log in XML Format

2021 ◽  
Vol 12 (3) ◽  
pp. 2623-2630
Author(s):  
Ang Jin Sheng Et.al
Keyword(s):  
Data Mining ◽  
Business Process ◽  
Accurate Result ◽  
Structured Data ◽  
Web Pages ◽  
Web Searching ◽  
General Application ◽  
Data Mining Techniques ◽  
Xml Documents ◽  
The Relationship

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.

A Study of XML Models for Data Mining

Data Mining ◽  
2013 ◽  
pp. 1-27
Author(s):  
Sangeetha Kutty ◽  
Richi Nayak ◽  
Tien Tran
Keyword(s):  
Data Mining ◽  
Data Model ◽  
Data Representation ◽  
Data Models ◽  
Data Mining Techniques ◽  
Xml Documents ◽  
The Future ◽  
Future Data

With the increasing number of XML documents in varied domains, it has become essential to identify ways of finding interesting information from these documents. Data mining techniques can be used to derive this interesting information. However, mining of XML documents is impacted by the data model used in data representation due to the semi-structured nature of these documents. In this chapter, we present an overview of the various models of XML documents representations, how these models are used for mining, and some of the issues and challenges inherent in these models. In addition, this chapter also provides some insights into the future data models of XML documents for effectively capturing its two important features, structure and content, for mining.

Building an Active Content Warehouse

2011 ◽  
pp. 63-95 ◽  
Author(s):  
Serge Abiteboul ◽  
Benjamin Nguyen ◽  
Gabriela Ruberg
Keyword(s):  
Web Service ◽  
Structured Data ◽  
Point Of View ◽  
Web Pages ◽  
Xml Documents ◽  
Runtime Environment ◽  
Embedded Web ◽  
New Type ◽  
Active Content ◽  
Active Xml

Non-quantitative content represents a large part of the information available nowadays, such as Web pages, e-mails, metadata about photos, etc. In order to manage this new type of information, we introduce the concept of content warehousing, the management of loosely structured data. The construction and maintenance of a content warehouse is an intricate task, involving many aspects such as feeding, cleaning and enriching semi-structured data. In this chapter, we introduce the Acware (for active content warehouse) specification language, whose goal is to help all sorts of users to organize content in a simple manner. The problem we are faced with is the following: The data are semi-structured, and the operations to be executed on this data may be of any sort. Therefore, we base our approach on XML to represent the data, and Web Services, as genericcomponents that can be tailored to specific applicative needs. In particular, we discuss the specification of mappings between the warehouse data and the parameters/results of services that are used to acquire and enrich the content. From the implementation point of view, an Acware specification of a content warehouse is compiled into a set of Active XML documents, i.e., XML documents with embedded Web service calls. These Active XML documents are then used to build and maintain the warehouse using the Active XML runtime environment. We illustrate the approach with a particular application drawn from microbiology and developed in the context of the French RNTL e.dot project.

A Study of XML Models for Data Mining

2011 ◽  
pp. 1-28
Author(s):  
Sangeetha Kutty ◽  
Richi Nayak ◽  
Tien Tran
Keyword(s):  
Data Mining ◽  
Data Model ◽  
Data Representation ◽  
Data Models ◽  
Data Mining Techniques ◽  
Xml Documents ◽  
The Future ◽  
Future Data

With the increasing number of XML documents in varied domains, it has become essential to identify ways of finding interesting information from these documents. Data mining techniques can be used to derive this interesting information. However, mining of XML documents is impacted by the data model used in data representation due to the semi-structured nature of these documents. In this chapter, we present an overview of the various models of XML documents representations, how these models are used for mining, and some of the issues and challenges inherent in these models. In addition, this chapter also provides some insights into the future data models of XML documents for effectively capturing its two important features, structure and content, for mining.

Research on the Data Model and the Approaches to Data Mining in the Semi-Structured Data

2014 ◽  
Vol 513-517 ◽  
pp. 663-666
Author(s):  
Feng Hua Liu
Keyword(s):  
Data Mining ◽  
Data Model ◽  
Structured Data ◽  
Large Database ◽  
The Relationship ◽  
Important Form

As an important form of Internet data, semi-structured data in data mining is an important fist conditions. And the data mining was designed to find and extract large database in the implied information of value. This paper first introduced the half structured data concept characteristic, based on the data from each of the half structural said, the data model two half-and-half structured data model are introduced, finally summarizes semi-structured data model and the relationship between the data model before difference [1].

scholarly journals Application of Data Mining in the Analysis of Martial Arts Athlete Competition Skills and Tactics

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Lingrong Tao
Keyword(s):  
Data Mining ◽  
Martial Arts ◽  
Statistical Data ◽  
Practical Significance ◽  
Data Mining Techniques ◽  
Develop Technology ◽  
Competitive Success ◽  
Daily Training ◽  
Using Data ◽  
The Relationship

In martial arts, data mining technologies are used to describe and analyze the moves of athletes and changes in the process and sequences. Martial arts is a process in which athletes use all kinds of strengths and actions to make offensive and defensive changes according to the tactics of opponents. One such martial arts is Wushu arts as it has a long history in reference to Chinese martial arts. During the Wushu competition, Wushu athletes show their adaptability and technical level in complex, random, and nonlinear competitive abilities, organized and systematic skills, tactics, and position movement. Using data mining techniques, in-depth mining a particular type of martial arts competition technology and tactics behind statistical data, and using the data to find the law of change to solve some problems, for martial arts athletes in daily training to develop technology and tactics and improve competition results, is the practical significance of data mining in martial arts athletes competition. This research explored the relationship between goal-oriented and mental intensity and their effect on competitive success outcomes.

scholarly journals Data Mining Techniques Based Stock Record Management

2019 ◽  
pp. 505-509
Author(s):  
N. Vijayalakshmi ◽  
A. Baviya
Keyword(s):  
Data Mining ◽  
Business Process ◽  
Fast Moving ◽  
Frequent Pattern ◽  
Record Management ◽  
Data Mining Techniques ◽  
Factors Influencing ◽  
Business Support ◽  
Slow Moving ◽  
Stock Information

Our targets are to show signs of improvement basic leadership for enhancing deal, administrations and quality, which is helpful instrument for business support, speculation and reconnaissance. A methodology is actualized for mining examples of gigantic stock information to foresee factors influencing the clearance of items. For this gap the stock information in three distinct groups based on sold amounts Dead-Stock, Slow-Moving and Fast-Moving utilizing K- implies calculation or Hierarchical agglomerative calculation. After that Most Frequent Pattern calculation is executed to discover frequencies of property estimations of the relating things. Most Frequent Pattern gives visit examples of thing characteristics and furthermore gives deals incline in a minimal shape. Grouping and Most Frequent Pattern calculation can create increasingly valuable example from expansive stock information which is useful to get thing data for stock. Opportune recognizable proof of recently developing patterns is required in business process. Information mining procedures are most appropriate for the characterization, valuable examples extraction and predications which are vital for business support and basic leadership. Examples from stock information show advertise inclines and can be utilized in determining which has incredible potential for basic leadership, vital arranging.

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