Data mining for supporting IT management

Bozdogan, Can; Zincir-Heywood, A. Nur

doi:10.1109/noms.2012.6212079

Cited by 8 publications

(11 citation statements)

References 15 publications

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“…Likewise in the case studies of DM-KM application in the transportation sector, the compilation of the [30] research involve deploying KM to aid in financial risk prediction and detection [30,32]. In the technology industry, Bozdogan and Zincir-Heywood [5] and Pytel et al [39] employ KM to facilitate decision-making to enhance organisational effectiveness and efficiency [5,39]. In another example from the manufacturing industry, Packianather et al [38] research employs KM to uncover the firm's consumer unique purchasing behaviouralforecasting potential purchasing behaviour to facilitate the SME's sales and marketing strategies [38].…”

Section: Dm-km Case Studies In the Smes' Contextmentioning

confidence: 99%

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

2020

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A core subfield of knowledge management (KM) and data mining (DM) constitutes an integral part of the knowledge discovery in database process. With the explosion of information in the new digital age, research studies in the DM and KM continue to heighten up in the business organisations, especially so, for the small and medium enterprises (SMEs). DM is crucial in supporting the KM application as it processes the data to useful knowledge and KM role next, is to manage these knowledge assets within the organisation systematically. At the comprehensive appraisal of the large enterprise in the transportation sector and the SMEs across various industries-it was gathered that there is limited research case study conducted on the application of DM-KM on the transportation SMEs in specific. From the extensive review of the case studies, it was uncovered that majority of the organisations are not leveraging on the use of tacit knowledge and that the SMEs are adopting a more traditional use of ICTs to its KM approach. In addition, despite DM-KM is being widely implemented-the case studies analysis reveals that there is a limitation in the presence of an integrated DM-KM assessment to evaluate the outcome of the DM-KM application. This paper concludes that there is a critical need for a novel DM-KM assessment plan template to evaluate and ensure that the knowledge created and implemented are usable and relevant, specifically for the SMEs in the transportation sector. Therefore, this research paper aims to carry out an in-depth review

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Section: Dm-km Case Studies In the Smes' Contextmentioning

confidence: 99%

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

2020

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“…In its FAQ building part, a clustering method is proposed to group similar enquiries. Can Bozdogan et al proposed a system that extracts information from public resources automatically to generate a knowledge base that supports IT management teams by utilizing data mining techniques and information retrieval 8 . The CES+ clustering algorithm used in this system groups and reorganizes the experience data crawled from websites into similar problem/solution pairs.…”

Section: Related Workmentioning

confidence: 99%

Ontology-based Document Mining System for IT Support Service

Shanavas¹,

Asokan²

2015

Procedia Computer Science

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Information Technology (IT) is a vital and an integral part of every organization. IT executives are constantly faced with problems that are difficult to tackle and time consuming. Experience is required to solve these problems easier and faster. We can utilize case-based reasoning (CBR), data mining and information retrieval (IR) techniques to automate IT problem solving and experience management. In this paper, we propose an IT ontology-based system for semantic retrieval that increases the efficiency and quality of IT support service. The proposed approach retrieves similar problem/solution pairs based on the concepts in the query and performs better than the traditional keyword-based approach especially in cases where the keywords of the relevant documents do not match the keywords in the query.

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“…EMITS is based on an IR approach and employs machine learning algorithms to build as well as to search the experience knowledgebase. In our previous work, we demonstrated which machine learning algorithms could be used for clustering the experience information [27] and for optimizing the system [35]. In this paper, we aim to integrate these di®erent components and develop and evaluate our prototype system EMITS.…”

Section: Related Workmentioning

confidence: 99%

“…To select an e±cient clustering algorithm di®erent machine learning algorithms and distance measures are compared for the Text Clustering Engine [27]. After having the comparison between results of CESþ and other algorithms, we chose CESþ to be our clustering engine's algorithm due to its best results.…”

Section: Text Clustering Enginementioning

confidence: 99%

“…EMITS employs CESþ [27] as its clustering engine and MOGA [35] as its optimization engine complemented with a crawler, a database and a graphical user interface to automate the extraction, search and retrieval tasks for IT management. We have built and evaluated EMITS on three di®erent publicly available data sets, namely Princeton, Parallel and GoDaddy.…”

Section: Introductionmentioning

confidence: 99%

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EMITS: An Experience Management System for IT Management Support

Bozdogan

Zincir-Heywood

Zincir

2015

Int. J. Soft. Eng. Knowl. Eng.

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This research focuses on the identi¯cation of relevant experience required for solving IT (Information Technology) problems in small-to medium-sized enterprises. To achieve this, we integrated information retrieval techniques with clustering and optimization techniques to design and develop a custom-built Experience Management system for IT management support. We have built and evaluated our system on three di®erent publicly available data sets: Princeton, Parallels and GoDaddy. Results support that it is possible to provide the right mix of automation and manual activity for IT experience management while achieving a high accuracy.

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Data mining for supporting IT management

Cited by 8 publications

References 15 publications

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

Ontology-based Document Mining System for IT Support Service

EMITS: An Experience Management System for IT Management Support

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