Abstract
As big enterprises and consumers communicate, collaborate and conduct commerce almost at the speed of light using voice, data and video, information explosion (a term first used in 1941, according to the Oxford English Dictionary) has created a need for its accumulation, processing and integration to create “knowledge.” Knowledge processing, in turn, allows us to use the information to make strategic decisions and improve the efficiency of the processes involved. Therefore, knowledge processing systems, their theory and practice are receiving renewed focus. These systems include processes and activities such as cognition, knowledge production, learning, knowledge acquisition, reasoning, management and application. In this paper we discuss how knowledge processing can be viewed as manipulation of various knowledge structures and their transformation. We argue that efficient organization of knowledge processing has to be based on structure transformations of data represented in a symbolic form.
Highlights
Knowledge processing is a central problem of Artificial Intelligence (AI) and an urgent dilemma of contemporary society and especially, in business and industry.As Bray [1] writes, organizational knowledge processes deal with the creation, distribution, use and exchange of knowledge for purposes of value creation
They involve managing the intellectual capital of organizations. These processes are best understood with the ecology and ecosystem metaphors
Performative organizational knowledge is a knowledge ecology—a system consisting of many sources, venues, forms and species of knowledge agents in a symbiotic relationship of productive exchange and value creation
Summary
Knowledge processing is a central problem of Artificial Intelligence (AI) and an urgent dilemma of contemporary society and especially, in business and industry. As Bray [1] writes, organizational knowledge processes deal with the creation, distribution, use and exchange of knowledge for purposes of value creation. They involve managing the intellectual capital of organizations. These processes are best understood with the ecology and ecosystem metaphors. In order to process knowledge and derive value from it, we need to understand the relationship between data, information and knowledge and create knowledge structures. Burgin [2] knowledge is derived from information obtained from data resulting from study, experience or instruction. In this paper we present various structure transformation techniques for knowledge processing
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