Supporting self-evaluation in local government via Knowledge Discovery and Data mining

Kum, Hye‐Chung; Duncan, Dean; Stewart, C.J.

doi:10.1016/j.giq.2008.12.009

Cited by 21 publications

(14 citation statements)

References 6 publications

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“…Even though there are many studies have been carried out in the context of data process [11,12], limited studies have been observed in evaluating organizational data in relation to the organizational goals [2,3]. Therefore, it is important to identify the relationship of organizational data that relates to the organizational goals.…”

Section: B Dependency Relationship Of Organizational Data To the Orgmentioning

confidence: 99%

Ontology Based Framework to Configure the Organizational Goal Analysis and Decision-Making

Izhar¹

2017

IJITCS

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Abstract-Organizational data is essential to assist domain experts and entrepreneurs for decision making process in relation to the organizational goals but the trustworthiness of organizational data in relation to achieving the organizational goals is often questioned because of the vast amount of organizational data available. This paper proposes a methodology to evaluate organizational data that relates to the organizational goals. This refers to the importance of assisting the organization to utilize relevance of organizational data from the vast amount of available data for decision making to the organizational goals. The aim of this paper is to identify dependency relationship of organizational data that match to the organizational goals and to define a metrics as an analysis approach to measure organizational data to be considered relevant to the organizational goals. The experiment is present to implement the propose methodology in the context of Australian economy. The contribution of this paper will serve as a first step in evaluation approach and analysis of organizational data that relates to the achievement of the organizational goals.

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Section: B Dependency Relationship Of Organizational Data To the Orgmentioning

confidence: 99%

Ontology Based Framework to Configure the Organizational Goal Analysis and Decision-Making

Izhar¹

2017

IJITCS

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“…The use of KDD technology can greatly enhance governmental practices by sharing information between many diverse agencies in an effective way [13]. Authors claim that KM is linked to the management of people and that the use of information technologies and management practices is relevant to create an appropriate environment in which to share information and knowledge [14][15][16].…”

Section: Knowledge Managementmentioning

confidence: 99%

“…Strategic partnerships involving government and university can merge distinct knowledge pools and communities of practice into a richer knowledge environment [22]. Strong partnerships between government agencies and interdisciplinary teams at universities can provide access to required expertise [13]. This paper's context relies on this assumption.…”

Section: Knowledge Managementmentioning

confidence: 99%

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Performing Knowledge Requirements Analysis for Public Organisations in a Virtual Learning Environment: A Social Network Analysis Approach

Mp¹,

Rb²,

Aib³

et al. 2014

J Inform Tech Soft Engg

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This kind of activity is a type of knowledge discovery in databases (KDD). According to [10], KDD refers to the overall process of discovering useful knowledge from data. [10] emphasise that data mining refers to just a particular step in this process, which requires appropriate prior knowledge and proper interpretation of the results. Therefore, KDD still lacks management of generated knowledge. [11,12] present a variety of commercial and free data mining tools.

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“…；但有些文献中则将这两个概念严格出分开来 [4][5] [27][28] ，临床医学 [29][30] ，药理学 [31] 中应用。除了原有领域内的范围不断扩展，数据挖掘可以应用的领域也不断扩展。例如，近十年来，数据挖掘已经在国防安全 [3,32] 、制造业 [5,[33][34][35][36] 、供电系统 [4,[37][38] 、工程管理 [29,39] 、社会服务结构 [40][41][42] …”

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An overview of data mining

Wang

Qiao

2010

2010 8th World Congress on Intelligent Control and Automation

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With the rapid development of information technology, the scale of a database increasingly grows. The problem, how to translate the large number data in a database into useful information and knowledge, is concerned by the academies and industries.At this point, data mining emerges and receives great concerns from the information industry and the whole society. In this paper, we firstly describe the development history of the data mining technology. Then their main methods and the application fields are summarized, and the ways to realize data mining is given. Finally, their future trends are discussed.

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Supporting self-evaluation in local government via Knowledge Discovery and Data mining

Cited by 21 publications

References 6 publications

Ontology Based Framework to Configure the Organizational Goal Analysis and Decision-Making

Ontology Based Framework to Configure the Organizational Goal Analysis and Decision-Making

Performing Knowledge Requirements Analysis for Public Organisations in a Virtual Learning Environment: A Social Network Analysis Approach

An overview of data mining

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