The utility of clustering for knowledge management system by structuration theory.

Author:Lee, Ook
Position::Report
 
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  1. INTRODUCTION

    The theoretical basis for this paper draws on structuration theory (Giddens 1979, 1984). The attention is on how structuration theory can offer a new way of looking at societal change and ICT. A Walsham (2002)'s paper whose focus was on cross-cultural issues of ICT implementation regards "structure" as "memory traces in the human mind" and "Action draws on rules of behavior and ability to deploy resources and, in so doing, produces and reproduces structure". By defining structure as rules and resources, the structuration theory recursively implicated in the reproduction of social systems. Giddens (1984) attempts to treat human action and social structure as a duality rather than a dualism. In other words, action and structure are seen as two aspects of the same whole. Giddens comments that social systems should be regarded as widely variable in the degree of systemness that they display. Walsham (2002) argues that the structural properties of society often display enough systemness for its members to speak about shared symbols, norms, and values. Knowledge Management System maintainers see that their systemness triggers structures in everyday acts including the understanding of knowledge depository. Since knowledge depository has no milestones, the Knowledge Management System maintainers shall have a difficult time in structration and creating systemness. However there are aspects of human life that are universally desired upon and structuration theory simultaneously recognizes the validity of varied structures of different countries as well as the possibility of breaking the mold. When a particular software that clusters knowledge management systems is implemented the consequences include not only efficient new way of working but also new perspective on how the maintainers can behave differently from structures, which can lead to fundamental change such as adopting new structure; advance in understanding knowledge depository. Walsham (1993, p. 64) provides a general view of the role of ICT in the context of structuration theory as following:

    A theoretical view of computer-based information systems in contemporary organizations which arises from structuration theory is that they embody interpretative schemes, provide coordination and control facilities, and encapsulate norms. They are thus deeply implicated in the modalities that link social action and structure, and are drawn on in interaction, thus reinforcing or changing social structures.

    Structuration theory appears to be focused on reproduction of structure through processes of routinization of activity and thus reinforcement of existing structures. However, Giddens also emphasizes human knowledgeability, and the way in which human beings reflexively monitor their own actions, that of others, and consequences, both intended and unintended.

    It should be noted that ICT can reinforce the existing structure but change it. This is the reason that a software tool which clusters knowledge management systems is required and helpful for the maintainers.

  2. THE CASE OF KNOWLEDGE MANAGEMENT SYSTEMS

    Knowledge management systems usually consist of a knowledge base, data base, model base, operating engine, and user interface. However the term "knowledge depository" can be used to include elements in knowledge base, model base, and data base since these bases will have the same architecture as a collection of knowledge pieces (Liebowitz, 2000). The content of a knowledge depository of knowledge management systems makes the maintenance seem clueless compared to conventional software maintenance. In conventional software maintenance, the maintainer can utilize salient features and landmarks of the program code as long as she/he is familiar with the programming language, i.e., the control statements such as "for", "do while", "begin", "end", or "procedure", are good landmarks to distinguish a code section while reading the code. They help building the maintainer's mental model of the program code. In structured programming languages, the maintainer is able to predict the organization of the content. For example, the maintainer can recognize that a module is called by another module by simply reading the code. A structured programming language lets the developer write codes in modules, which in turn, makes the maintenance work easier by facilitating program comprehension. However, the knowledge pieces of a knowledge management system have no salient features or landmarks, i.e., every code is composed of natural language texts. The goal of this research is to develop a tool for knowledge management system maintenance. This tool structures the natural language_based knowledge pieces by clustering knowledge pieces using a neural network algorithm called a Hopfield net. With this tool available, the job of maintaining a knowledge management system can be less cumbersome since the maintainer can understand the knowledge depository more easily and locate the target knowledge piece quickly.

  3. KNOWLEDGE DEPOSITORY CLUSTERING FOR KNOWLEDGE MANAGEMENT SYSTEM UNDERSTANDING

    3.1 Program Comprehension Vs. Knowledge Depository Comprehension

    Program comprehension is said to be a major factor in providing effective maintenance of conventional software systems. Sharon (1996) pointed out that excessive time is spent learning and figuring out the code. In other words, the maintainer of conventional software spends significant time just to figure out what the code is all about. This analysis step makes the maintenance process less efficient. Thus, such tools as program scanner, program navigator, and logic flow tracer, trace the logic and data flows and allow browsing within and among system components. Since knowledge depository comprehension is as important in knowledge management system maintenance as program comprehension in conventional software maintenance, a tool that facilitates the understanding of knowledge pieces should be beneficial. What makes knowledge depository comprehension easier should be identified first before we set out to construct such a tool. We can utilize gains from research on program comprehension in conventional software maintenance. Mayrhauser and Vans (1995) identify the understanding mechanism(chunking) as an important element of the mental model. Chunking creates...

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