Showing papers on "Domain knowledge published in 2000"

Enabling Knowledge Creation: How to Unlock the Mystery of Tacit Knowledge and Release the Power of Innovation

Abstract: When The Knowledge-Creating Company (OUP; nearly 40,000 copies sold) appeared, it was hailed as a landmark work in the field of knowledge management. Now, Enabling Knowledge Creation ventures even further into this all-important territory, showing how firms can generate and nurture ideas by using the concepts introduced in the first book. Weaving together lessons from such international leaders as Siemens, Unilever, Skandia, and Sony, along with their own first-hand consulting experiences, the authors introduce knowledge enabling-the overall set of organizational activities that promote knowledge creation-and demonstrate its power to transform an organization's knowledge into value-creating actions. They describe the five key "knowledge enablers" and outline what it takes to instill a knowledge vision, manage conversations, mobilize knowledge activists, create the right context for knowledge creation, and globalize local knowledge. The authors stress that knowledge creation must be more than the exclusive purview of one individual-or designated "knowledge" officer. Indeed, it demands new roles and responsibilities for everyone in the organization-from the elite in the executive suite to the frontline workers on the shop floor. Whether an activist, a caring expert, or a corporate epistemologist who focuses on the theory of knowledge itself, everyone in an organization has a vital role to play in making "care" an integral part of the everyday experience; in supporting, nurturing, and encouraging microcommunities of innovation and fun; and in creating a shared space where knowledge is created, exchanged, and used for sustained, competitive advantage. This much-anticipated sequel puts practical tools into the hands of managers and executives who are struggling to unleash the power of knowledge in their organization.

WHITE PAPER Knowing What We Know: Supporting Knowledge Creation and Sharing in Social Networks

Abstract: Many early knowledge management initiatives focused heavily on informationtechnology and codified knowledge and so missed performance improvementopportunities from interventions targeting knowledge embedded within networks ofemployees. Despite advanced technical solutions employed to manage organizationalknowledge, we continue to find that people are often more reliant on other people thanthey are on databases when seeking answers to unstructured questions. As a result,organizations creating more cohesive networks on knowledge related dimensions arebetter able to collectively solve problems, create new knowledge and transfer explicit andtacit knowledge embodied within employees. The following article reports on a cross-industry research program assessing ways to promote knowledge creation and transfer innetworks of employees. Specifically, we have found four characteristics of relationshipsimportant for knowledge creation in networks: 1) knowing what others know; 2) havingaccess to other people’s thinking; 3) having people be willing to actively engage inproblem solving; and 4) having a safe relationship to promote learning and creativity.Mapping these dimensions in social networks yields targeted social and technicalinterventions managers can employ to improve a network’s ability to create and shareknowledge.

Hierarchies and the Organization of Knowledge in Production

Abstract: This paper studies how communication allows for the specialized acquisition of knowledge. It shows that a knowledge-based hierarchy is a natural way to organize the acquisition of knowledge when matching problems with those who know how to solve them is costly. In such an organization, production workers acquire knowledge about the most common or easiest problems confronted, and specialized problem solvers deal with the more exceptional or harder problems. The paper shows that the model is consistent with stylized facts in the theory of organizations and uses it to analyze the impact of changes in production and information technology on organizational design.

The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility

Abstract: Knowledge-based systems have become ubiquitous in recent years. Knowledge-base developers need to be able to share and reuse knowledge bases that they build. Therefore, interoperability among different knowledge-representation systems is essential. The Open Knowledge-Base Connectivity protocol (OKBC) is a common query and construction interface for frame-based systems that facilitates this interoperability. ProtEgE-2000 is an OKBC-compatible knowledge-base-editing environment developed in our laboratory. We describe ProtEgE-2000 knowledge model that makes the import and export of knowledge bases from and to other knowledge-base servers easy. We discuss how the requirements of being a usable and configurable knowledge-acquisition tool affected our decisions in the knowledge-model design. ProtEgE-2000 also has a flexible metaclass architecture which provides configurable templates for new classes in the knowledge base. The use of metaclasses makes ProtEgE-2000 easily extensible and enables its use with other knowledge models. We demonstrate that we can resolve many of the differences between the knowledge models of ProtEgE-2000 and Resource Description Framework (RDF)--a system for annotating Web pages with knowledge elements--by defining a new metaclass set. Resolving the differences between the knowledge models in declarative way enables easy adaptation of ProtEgE-2000 as an editor for other knowledge-representation systems.

Neuro-fuzzy rule generation: survey in soft computing framework

Abstract: The present article is a novel attempt in providing an exhaustive survey of neuro-fuzzy rule generation algorithms. Rule generation from artificial neural networks is gaining in popularity in recent times due to its capability of providing some insight to the user about the symbolic knowledge embedded within the network. Fuzzy sets are an aid in providing this information in a more human comprehensible or natural form, and can handle uncertainties at various levels. The neuro-fuzzy approach, symbiotically combining the merits of connectionist and fuzzy approaches, constitutes a key component of soft computing at this stage. To date, there has been no detailed and integrated categorization of the various neuro-fuzzy models used for rule generation. We propose to bring these together under a unified soft computing framework. Moreover, we include both rule extraction and rule refinement in the broader perspective of rule generation. Rules learned and generated for fuzzy reasoning and fuzzy control are also considered from this wider viewpoint. Models are grouped on the basis of their level of neuro-fuzzy synthesis. Use of other soft computing tools like genetic algorithms and rough sets are emphasized. Rule generation from fuzzy knowledge-based networks, which initially encode some crude domain knowledge, are found to result in more refined rules. Finally, real-life application to medical diagnosis is provided.

Web search behavior of Internet experts and newbies

Abstract: Searching for relevant information on the World Wide Web is often a laborious and frustrating task for casual and experienced users. To help improve searching on the Web based on a better understanding of user characteristics, we investigate what types of knowledge are relevant for Web-based information seeking, and which knowledge structures and strategies are involved. Two experimental studies are presented, which address these questions from different angles and with different methodologies. In the first experiment, 12 established Internet experts are first interviewed about search strategies and then perform a series of realistic search tasks on the World Wide Web. From this study a model of information seeking on the World Wide Web is derived and then tested in a second study. In the second experiment two types of potentially relevant types of knowledge are compared directly. Effects of Web experience and domain-specific background knowledge are investigated with a series of search tasks in an economics-related domain (introduction of the Euro currency). We find differential and combined effects of both Web experience and domain knowledge: while successful search performance requires the combination of the two types of expertise, specific strategies directly related to Web experience or domain knowledge can be identified.

FLAME—Fuzzy Logic Adaptive Model of Emotions

Abstract: Emotions are an important aspect of human intelligence and have been shown to play a significant role in the human decision-making process. Researchers in areas such as cognitive science, philosophy, and artificial intelligence have proposed a variety of models of emotions. Most of the previous models focus on an agent's reactive behavior, for which they often generate emotions according to static rules or pre-determined domain knowledge. However, throughout the history of research on emotions, memory and experience have been emphasized to have a major influence on the emotional process. In this paper, we propose a new computational model of emotions that can be incorporated into intelligent agents and other complex, interactive programs. The model uses a fuzzy-logic representation to map events and observations to emotional states. The model also includes several inductive learning algorithms for learning patterns of events, associations among objects, and expectations. We demonstrate empirically through a computer simulation of a pet that the adaptive components of the model are crucial to users' assessments of the believability of the agent's interactions.

Knowledge value chain

Abstract: Introduces the knowledge value chain model as a knowledge management (KM) framework. The model consists of knowledge infrastructure (knowledge worker recruitment, knowledge storage capacity, customer/supplier relationship and CKO and management), the process of KM (knowledge acquisition, knowledge innovation, knowledge protection, knowledge integration, and knowledge dissemination), and the interaction among those components resulting in knowledge performance. Further to the discussion of knowledge value chain (KVC), the following viewpoint was proposed: KM guides the way a corporation performs individual knowledge activities and organizes its entire KVC. It was suggested that competitive advantage grows out of the way corporations organize and perform discrete activities in knowledge value chain which should be measured by the core competence of corporation. This article also provides a cross‐reference for e‐commerce researchers and practitioners.

Knowledge Engineering and Management

Abstract: The disciplines of knowledge engineering and knowledge management are closely tied. Knowledge engineering deals with the development of information systems in which knowledge and reasoning play pivotal roles. Knowledge management, a newly developed field at the intersection of computer science and management, deals with knowledge as a key resource in modern organizations. Managing knowledge within an organization is inconceivable without the use of advanced information systems; the design and implementation of such systems pose great organization as well as technical challenges. The book covers in an integrated fashion the complete route from corporate knowledge management, through knowledge analysis and engineering, to the design and implementation of knowledge-intensive information systems. The CommonKADS methodology, developed over the last decade by an industry-university consortium led by the authors, is used throughout the book. CommonKADS makes as much use as possible of the new UML notation standard. Beyond information systems applications, all software engineering and computer systems projects in which knowledge plays an important role stand to benefit from the CommonKADS methodology.

Organizing knowledge in the knowledge development cycle

Abstract: The main aim of the paper is to examine some of the strategies that can be matched to increase the effectiveness of the knowledge development cycle. In manufacturing and operational works, the effectiveness of different organizing strategies to enhance the quality of manufacturing processes and products is well established. In knowledge works, however, we lack such frameworks. Unlike manufacturing and operational processes, knowledge development processes are often chaotic, unstructured, and unsystematic, resulting in intangible products. Therefore, the principles of manufacturing strategies cannot be applied in the knowledge development cycle. In knowledge works, organizing strategies should be defined and initiated based on knowledge development phases (e.g. knowledge creation, knowledge adoption, knowledge distribution, and knowledge review and revision). Each phase, in the knowledge development cycle, needs to be evaluated in context of its characteristics on repetition, standardization, reliability, and specifications.

A framework of knowledge management systems: issues and challenges for theory and practice

Abstract: As the basis of value creation increasingly depends on the leverage of the intangible assets of firms, knowledge management systems (KMS) are emerging as powerful sources of competitive advantage However, the general recognition of the importance of such systems seems to be accompanied by a technology-induced drive to implement systems with inadequate consideration of the fundamental knowledge problems that the KMS are likely to solve This paper contributes to the stream of research on knowledge management systems by proposing an inductively developed framework for this important class of information systems, classifying KMS based on the locus of the knowledge and the a priori structuring of contents This framework provides a means to explore issues related to KMS and unifying dimensions underlying different types of KMS The contingencies that we discuss—the size and diversity of networks, the maintenance of knowledge flows and the long term effects of the use of KMS—provide a window into work in a number of reference disciplines that would enrich the utility of KMS and also open up fruitful areas for future research

Automatic acquisition of domain knowledge for Information Extraction

Abstract: In developing an Information Extraction (IE) system for a new class of events or relations, one of the major tasks is identifying the many ways in which these events or relations may be expressed in text. This has generally involved the manual analysis and, in some cases, the annotation of large quantities of text involving these events. This paper presents an alternative approach, based on an automatic discovery procedure, EXDISCO, which identifies a set of relevant documents and a set of event patterns from un-annotaled text, starting from a small set of "seed patterns." We evaluate EXDISCO by comparing the performance of discovered patterns against that of manually constructed systems on actual extraction tasks.

The logic of knowledge bases

Abstract: The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge -- a knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest. This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it.

Knowledge and Communities

Abstract: From the Publisher: Knowledge and Communities is the first book dedicated to a major new knowledge management topic. "Communities of Practice" are cross-organizational groups of people sharing knowledge, solving common problems, and exchanging insights and frustrations. Knowledge and Communities, a collection of authoritative articles, describes the dynamics of these groups and explains how they enable organizational knowledge to be creating, shared, and applied. Features: Hot-topic - addresses how virtual/on-line communities drive an organization's e-commerce and knowledge strategies Establishes best practices for building and maintaining traditional and virtual communities

Integrated analysis and design of knowledge systems and processes

Abstract: Although knowledge management has been investigated in the context of decision support and expert systems for over a decade, interest in and attention to this topic have exploded recently. But integration of knowledge process design with knowledge system design is strangely missing from the knowledge management literature and practice. The research described in this chapter focuses on knowledge management and system design from three integrated perspectives: 1 reengineering process innovation, 2 expert systems knowledge acquisition and representation, and 3 information systems analysis and design. Through careful analysis and discussion, we integrate these three perspectives in a systematic manner, beginning with analysis and design of the enterprise process of interest, progressively moving into knowledge capture and formalization, and then system design and implementation. Thus, we develop an integrated approach that covers the gamut of design considerations from the enterprise process in the large, through alternative classes of knowledge in the middle, and on to specific systems in the detail. We show how this integrated methodology is more complete than existing developmental approaches and illustrate the use and utility of the approach through a specific enterprise example, which addresses many factors widely considered important in the knowledge management environment. Using the integrated methodology that we develop and illustrate in this article, the reader can see how to identify, select, compose and integrate the many component applications and technologies required for effective knowledge system and process design.

Uml as domain specific language for the construction of knowledge-based configuration systems

Abstract: In many domains, software development has to meet the challenges of developing highly adaptable software very rapidly. In order to accomplish this task, domain specific, formal description languages and knowledge-based systems are employed. From the viewpoint of the industrial software development process, it is important to integrate the construction and maintenance of these systems into standard software engineering processes. In addition, the descriptions should be comprehensible for the domain experts in order to facilitate the review process. For the realization of product configuration systems, we show how these requirements can be met by using a standard design language (UML-Unified Modeling Language) as notation in order to simplify the construction of a logic-based description of the domain knowledge. We show how classical description concepts for expressing configuration knowledge can be introduced into UML and be translated into logical sentences automatically. These sentences are exploited by a general inference engine solving the configuration task.

Genetic programming as a model induction engine

Abstract: Present day instrumentation networks already provide immense quantities of data, very little of which provides any insights into the basic physical processes that are occurring in the measured medium. This is to say that the data by itself contributes little to the knowledge of such processes. Data mining and knowledge discovery aim to change this situation by providing technologies that will greatly facilitate the mining of data for knowledge. In this new setting the role of a human expert is to provide domain knowledge, interpret models suggested by the computer and devise further experiments that will provide even better data coverage. Clearly, there is an enormous amount of knowledge and understanding of physical processes that should not be just thrown away. Consequently, we strongly believe that the most appropriate way forward is to combine the best of the two approaches: theory-driven, understanding-rich with data-driven discovery process. This paper describes a particular knowledge discovery algorithm—Genetic Programming (GP). Additionally, an augmented version of GP—dimensionally aware GP—which is arguably more useful in the process of scientific discovery is described in great detail. Finally, the paper concludes with an application of dimensionally aware GP to a problem of induction of an empirical relationship describing the additional resistance to flow induced by flexible vegetation.

Towards an effective cooperation of the user and the computer for classification

Abstract: trees have been successfully used for the task of classifi- cation. However, state-of-the-art algorithms do not incorporate the user in the tree construction process. This paper presents a new user-centered approach to this process where the user and the com- puter can both contribute their strengths: the user provides domain knowledge and evaluates intermediate results of the algorithm, the computer automatically creates patterns satisfying user constraints and generates appropriate visualizations of these patterns. In this cooperative approach, domain knowledge of the user can direct the search of the algorithm. Additionally, by providing adequate data and knowledge visualizations, the pattern recognition capabilities of the human can be used to increase the effectivity of decision tree construction. Furthermore, the user gets a deeper understanding of the decision tree than just obtaining it as a result of an algorithm. To achieve the intended level of cooperation, we introduce a new visu- alization of data with categorical and numerical attributes. A novel technique for visualizing decision trees is presented which provides deep insights into the process of decision tree construction. As a key contribution, we integrate a state-of-the-art algorithm for deci- sion tree construction such that many different styles of cooperation - ranging from completely manual over combined to completely automatic classification - are supported. An experimental perfor- mance evaluation demonstrates that our cooperative approach yields an efficient construction of decision trees that have a small size, but a high accuracy.

The KRAFT architecture for knowledge fusion and transformation

Abstract: This paper describes the Knowledge Reuse And Fusion/Transformation (KRAFT) architecture which supports the fusion of knowledge from multiple, distributed, heterogeneous sources. The architecture uses constraints as a common knowledge interchange format, expressed against a common ontology. Knowledge held in local sources can be transformed into a common constraint language, and fused with knowledge from other sources. The fused knowledge is then used to solve some problem or deliver some information to a user. Problem solving in KRAFT typically exploits pre-existing constraint solvers. KRAFT uses an open and flexible agent architecture in which knowledge sources, knowledge fusing entities and users are all represented by independent KRAFT agents, communicating using a messaging protocol. Facilitator agents perform matchmaking and brokerage services between the various kinds of agent. KRAFT is being applied to an example application in the domain of network data services design.

Design repositories: engineering design's new knowledge base

Abstract: Driven by pressure to reduce product development time, industry has started looking for new ways to exploit stores of engineering artifact knowledge. Engineers are increasingly turning to design repositories as knowledge bases to help them represent, capture, share and reuse corporate design knowledge. The paper discusses the NIST Design Repository Project.

Expertise and category-based induction.

Abstract: The authors examined inductive reasoning among experts in a domain. Three types of tree experts (landscapers, taxonomists, and parks maintenance personnel) completed 3 reasoning tasks. In Experiment 1, participants inferred which of 2 novel diseases would affect "more other kinds of trees" and provided justifications for their choices. In Experiment 2, the authors used modified instructions and asked which disease would be more likely to affect "all trees." In Experiment 3, the conclusion category was eliminated altogether, and participants were asked to generate a list of other affected trees. Among these populations, typicality and diversity effects were weak to nonexistent. Instead, experts' reasoning was influenced by "local" coverage (extension of the property to members of the same folk family) and causal-ecological factors. The authors concluded that domain knowledge leads to the use of a variety of reasoning strategies not captured by current models of category-based induction.

Knowledge management in small enterprises

Abstract: This paper investigates the extent to which six factors drawn from the theory and practice of knowledge management can be applied in small organisations. The factors are: balance between need and cost of knowledge acquisition; the extent to which knowledge originates in the external environment; internal knowledge processing; internal knowledge storage; use and deployment of knowledge within the organisation; and attention to human resources. Three cases demonstrate that the fundamental concepts and principles of knowledge management are similar for small and large organisations. Differences include the value placed on systematic knowledge management practices such as formalised environmental scanning and computer‐based knowledge sharing systems. Consultants, and library and information professionals, are advised to understand the organisation’s management and communication culture; emphasise simple and inexpensive systems integrated into everyday practice; and establish and monitor adherence to tools suc...

Knowledge objects and mental models

Abstract: This paper describes knowledge components that are thought to be appropriate and sufficient to precisely describe certain types of cognitive subject matter content (knowledge). It also describes knowledge structures that show the relationships among these knowledge components and among other knowledge objects. It suggests that a knowledge structure is a form of schema such as those that learners use to represent knowledge in memory. A mental model is a schema plus cognitive processes for manipulating and modifying the knowledge stored in a schema. We suggested processes that enable learners to manipulate the knowledge components of conceptual network knowledge structures for purposes of classification, generalization, and concept elaboration. We further suggested processes that enable learners to manipulate the knowledge components of process knowledge structures (PEAnets) for purposes of explanation, prediction, and troubleshooting. The hypothesis of this paper is that knowledge components and knowledge structures, such as those described in this paper, could serve as meta mental models that would enable learners to more easily acquire conceptual and causal networks and their associated processes. The resulting specific mental models would facilitate their ability to solve problems of conceptualization and interpretation.

From learning organisation to knowledge entrepreneur

Abstract: Establishes the clear link between learning and knowledge, and proposes a simple model, which makes this relationship explicit. A range of definitions of the learning organisation are drawn from the literature. Much of this literature makes little reference to that which is being learned although those authors who have introduced the concepts of the learning laboratory, the knowledge creating organisation and the knowing organisation acknowledge the significance of knowledge in organisational development and learning. Other perspectives on the organisational processes associated with knowledge come from the recent literature on knowledge management. It is argued that indiscriminate knowledge creation will not lead to organisational learning, and that knowledge is not something that can be viewed as a neutral tool in the learning process. A number of characteristics of knowledge need to be recognised, and accommodated in learning processes and knowledge management. Finally, the concept of a knowledge entrepreneur is proposed.

Creating design knowledge: from research into practice

Abstract: This paper considers how we create design knowledge. It examines the ways that research contributes to design knowledge in theory and in practice. The paper will ask seven important questions: What is the nature of design? How does the nature of design involve knowledge of certain kinds? What are the sources of knowledge? How does research function as a source of knowledge? How does research relate to other sources of knowledge? How do we create design knowledge through research? How does new knowledge move from research into practice? The paper will outline answers to these questions. It will also provide information and resources for those who want to explore further.

Information dynamics, learning and knowledge creation in organizations

Abstract: Managers in a wide array of organizations are concentrating on knowledge creation as a way to achieve competitiveness. Organizational knowledge, they hope, enables them to bring innovative products/services continuously in the marketplace. However, many are finding it difficult to understand how organizations create knowledge. By using the concepts of individual learning capability and the learning culture of organizations, the present study shows how the sum of individual knowledge does not equate to organizational knowledge. This distinction between individual knowledge and organizational knowledge is an important one, as a majority of studies do not clearly show how individual knowledge is different from organizational knowledge. The study also offers a set of suggestions to managers to develop a learning culture in the organizations.