An autonomous knowledge acquisition system toward the ubiquitous knowledge management

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An autonomous knowledge acquisition system toward the ubiquitous knowledge management

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Abstract

Knowledge management (KM), which pursues dynamic knowledge creation and sharing within and among organizations, had been boomed since the end of the last century. However, because of some technical limitations as well as cultural barriers, the concept of KM has been getting buried alive, nowadays, in spite of its tremendous potentials to organizations. One of the most serious problems that conventional KM has been pointed out tardy and ineffective acquisition of knowledge, which initiates the tragedy in knowledge revolution. Without knowledge to be managed, naturally the usability of knowledge management must be doubted. Therefore, this paper suggests an amended KM framework, especially focused on the autonomous knowledge acquisition process. The suggested methodology for knowledge acquisition is basically processed in an automated manner, but follows the same pattern of human experts' activities for acquiring knowledge by deploying the capabilities of ubiquitous computing technologies. Based on the proposed methodology, this paper also clarifies the relationship between context and knowledge, and hence defines the concept of contextual knowledge. To validate the feasibility of the proposed concepts, CKAS (Context-based Knowledge Acquisition System), a prototype system, is implemented.

Abstract
Introduction
Related literatures
1. Research to automate the process for knowledge acquisition
2. Research to minimize user's computing activity
3. Research to utilize context
4. Research to manage knowledge based on context
Conceptual framework
Ubiquitous computing technology-based KMS (ubiKMS)
1. Context acquisition subsystem
2. Context inference subsystem
3. Ontology base subsystem
Prototype implementation: Context-based Knowledge Acquisition System (CKAS)
1. Speech-to-text module
2. Word steaming module
3. Word vector tool
4. SVM module
5. Performance
Concluding remarks
References

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[...] Therefore, a new computing pattern that promotes autonomous knowledge acquisition with considering the quality of the acquired Research to utilize context The context aware computing is a new computing paradigm which deploys the concept of context as well of the functionality of autonomous automation. Using context, users can experience more user-centric, therefore friendly, services in an unconscious and convenient manner. A context aware application adapts according to the location of use, the collection of nearby people, hosts, and accessible devices, as well as to changes to such things over time (Schilit et al., 1994). [...]

[...] By storing knowledge with its context using the ontology, more autonomous expansion of knowledge as well as accurate application of knowledge can be expected Prototype Implementation: Context-based Knowledge Acquisition System (CKAS) The prototype system is focused on the knowledge acquisition process only. Based on the context acquisition subsystem and context inference subsystem, the prototype system is designed to automatically sense and infer the context so that knowledge can be accumulated without human involvement. Fig.5 shows the workflows of the prototype system. [...]

[...] Conventionally, knowledge acquisition has been processed manually by related staffs and experts or automatically by the knowledge management system (KMS) itself. Up-to-date the efficiency of the automatic knowledge acquisition is still unsatisfactory due to over-complex algorithms and immature methodology (Yan et al., 2004). Because automated acquisition could not effectively, namely appropriately, gather knowledge which resides in the human brain, inevitably manual acquisition should be performed (Edwards et al., 2004). Meanwhile, the accuracy of the acquired knowledge using manual KA tends to be questionable as the information is collected from a very limited number of experts with their expertise refrained in very specific and narrow fields (Yan et al., 2004). [...]

[...] (2004), “Adding Context-awareness to Knowledge Management in Modern Enterprises”, Proceeding of the 2nd IEEE International Conference on Intelligent Systems, 393-398 (Joachims, 1998) Joachims, T. (1998), “Text categorization with support vector machines: Learning with many relevant features”, Proceedings of the European Conference on Machine Learning (Jojic et al., 2000) Jojic, N., Brumitt, B., Meyers, B., Harris, S., and Huang, T. (2000), “Detection and estimation of pointing gestures in dense disparity Proceedings of the 4th IEEE International Conference, 468-475 (Khedr and Karmouch, 2004) Khedr, M. [...]

[...] Once a keyword is identified, SVM classifies it into one of predefined categories by comparing it with each word of the branches Ubiquitous computing technology-based KMS (ubiKMS) A system for context-based knowledge acquisition will certainly contribute the fertilized utilization of KMS, because truly automated and accurate acquisition of knowledge can be enabled. It can relieve human efforts to register knowledge as well as improve the quality of knowledge by considering the context of use. It is stated that ubiquitous computing-based information systems (ubiISs) usually have the capabilities of invisibility, mobility, nomadicity, portability, proactiveness, and embeddedness in their operation (Hong et al., 2004; Kwon et al., 2005; 2006). [...]

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