Knowledge acquisition for decision support systems on an electronic assembly line

Gebus, Sébastien; Leiviskä, Kauko

doi:10.1016/j.eswa.2007.09.058

Cited by 51 publications

(25 citation statements)

References 23 publications

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“…The importance of this aspect of user interaction is listed as a critical success factor in the implementation of BI systems in an organization [43]. The complexity of any interface must be sufficient to present the full scope of information, while keeping the data extraction process as simple as possible [32]. This highlights the importance of applying usability principles to the design of BI application interfaces.…”

Section: Usability In Business Intelligencementioning

confidence: 99%

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Usability Evaluation for Business Intelligence Applications: A User Support Perspective

Jooste¹,

Biljon²,

Mentz³

2014

SACJ

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Business Intelligence (BI) applications provide business information to drive decision support. Usability is one of the factors determining the optimal use and eventual benefit derived from BI applications. The documented need for more BI usability research together with the practical necessity for BI evaluation guidelines in the mining industry provides the rationale for this study. The purpose of the study was to investigate the usability evaluation of BI applications in the context of a coal mining organization. The research is guided by the question: How can existing usability criteria be customized to evaluate the usability of BI applications. The research design included user observation, heuristic evaluation and a survey. Based on observations made during user support on a BI application used at a coal mining organization a log of usability issues was compiled. The usability issues extracted from this log was compared and contrasted with general usability criteria from literature to synthesize an initial set of BI usability evaluation criteria. These criteria were used as the basis for a heuristic evaluation of the BI application used at the coal mining organization. The same BI application was also evaluated using the Software Usability Measurement Inventory (SUMI) standardized questionnaire. The results from the two evaluations were triangulated and then compared with the BI user issues again to contextualize the findings and synthesize a validated and refined set of criteria. The main contribution of the study is the usability evaluation criteria for BI applications presented as guidelines. These guidelines deviate from existing evaluation guidelines in the emphasis on information architecture, learnability and operability.

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Section: Usability In Business Intelligencementioning

confidence: 99%

“…This culminates in the goals of effectiveness, efficiency, safety, utility, learnability and memorability [28]. The measurement of usability depends on the users, their needs (goals) and the context -three variables that are inconsistent and unstable in themselves [32]. The focus of HCI research has evolved over time [33].…”

Section: Usabilitymentioning

confidence: 99%

Usability Evaluation for Business Intelligence Applications: A User Support Perspective

Jooste¹,

Biljon²,

Mentz³

2014

SACJ

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“…A substantial number of papers related to knowledge based systems (KBS) have been published since the early 1990s (Kandil et al, 1992;Paton et al, 2000;Lai, 2007;Wen et al, 2008;Qian et al, 2009;Choi, 2009;Gebus & Leiviska, 2009;Pirró et al, 2009). In these papers, emphasis has been given mainly to the collection, management and application of the knowledge using information technology.…”

Section: Knowledge Based Systemmentioning

confidence: 99%

Model-based computer-aided framework for design of process monitoring and analysis systems

Singh

Gernaey

Gani

2009

Computers & Chemical Engineering

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“…Studies continuation of data mining in the semiconductor fabrication process in 2007 can be found in (Chien, C. et al, 2007). (Gebus, S. et al, 2009) present knowledge acquisition software implemented for decision support system on electronic assembly line, that supports portability and flexibility.…”

Section: Industrial Data Mining Applications Overviewmentioning

confidence: 99%

Data Mining Industrial Applications

Wójcik¹,

Gromaszek²

2011

Knowledge-Oriented Applications in Data Mining

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Knowledge acquisition for decision support systems on an electronic assembly line

Cited by 51 publications

References 23 publications

Usability Evaluation for Business Intelligence Applications: A User Support Perspective

Usability Evaluation for Business Intelligence Applications: A User Support Perspective

Model-based computer-aided framework for design of process monitoring and analysis systems

Data Mining Industrial Applications

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