Web Content Mining Focused on Named Objects

Snåšel, Václav; Kudělka, Miloš

doi:10.1007/978-81-8489-203-1_3

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…This, coupled with the stellar advances in computing technologies, really improved the image of ''data mining''. The web is the largest dynamic and online store known today, and web mining refers to the process of extracting knowledge from web pages by exploring their contents, the hyperlinks that connect these pages, or usage patterns of users (Sná sel and Kudelka, 2009). This paper did not discuss CBM as these methods do not involve any interaction with an expert and thus fall outside the focus of this paper; however, they might be of interest to knowledge managers.…”

Section: Discussionmentioning

confidence: 99%

Knowledge elicitation techniques in a knowledge management context

Gavrilova

Andreeva

2012

Journal of Knowledge Management

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Purpose -A significant part of knowledge and experience in an organization belongs not to the organization itself, but to the individuals it employs. Therefore, knowledge management (KM) tasks should include eliciting knowledge from knowledgeable individuals. The paper aims to argue that the current palette of methods proposed for this in KM discourse is limited by idealistic assumptions about the behavior of knowledge owners. This paper also aims to enrich the repertoire of methods that can be used in an organization to extract knowledge (both tacit and explicit) from its employees by bridging KM and knowledge engineering and its accomplishments in the knowledge elicitation field.Design/methodology/approach -This paper is based on extensive literature review and 20 years of experience of one of the authors in applying various knowledge elicitation techniques in multiple companies and contexts.Findings -The paper proposes that the special agent (analyst) might be needed to elicit knowledge from individuals (experts) in order to allow further knowledge sharing and knowledge creation. Based on this idea, the paper proposes a new classification of the knowledge elicitation techniques that highlights the role of analyst in the knowledge elicitation process.Practical implications -The paper contributes to managerial practice by describing a systemic variety of knowledge elicitation techniques with direct recommendations of their feasibility in the KM context.Originality/value -The paper contributes to a wider use of knowledge engineering methodologies and technologies by KM researchers and practitioners in organizations.

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Section: Discussionmentioning

confidence: 99%