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Knowledge Sharing Model of 24-Hour Knowledge Factory
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Focuses on the distinction between the explicit and implicit types of knowledge. Discussion on fragmentation and the positivists theory; Details on the epistemological model developed for representing several types of knowledge; Conclusions.ABSTRACT FROM AUTHOR There is much interest in organizational knowledge following the recognition of its strategic place in inter-firm competition, but there is no adequate theory of such knowledge, or of its acquisition, storage and application. Penrose's (1959) theor y of the growth of the firm, Nelson and Winter's (1982) evolutionary economics, and the gestalt notions of discontinuous perceptual change taken from Lewin (1935), still define the cutting edge of the learning and knowledge-based approaches to the firm. Compared with these field-shaping works, the recent literature on organizational knowledge, learning and memory seems inconclusive. Takes a new start from the Jamesian distinction between knowing what and knowing how, and the Durkheimian distinction betw een individual and social forms of knowledge. The resulting pluralistic organizational epistemology implies a dynamic theory of the firm as a dialectical system of knowledge processes.ABSTRACT FROM AUTHOR
A growing number of companies are opting to perform increasing types of professional services in foreign countries, creating, for some companies, unprecedented opportunities to reduce costs and nucleate strategic relationships, while, for others, representing a major threat to current prosperity. Outsourcing and Offshoring of Professional Services: Business Optimization in a Global Economy discusses the considerations and implications surrounding the outsourcing and offshoring of professional services, such as software development computer-aided design, and healthcare, from multiple global perspectives. This Premier Reference Source, offering industry professionals, policymakers, students, and educators with a balance between a broad overview and detailed analysis of offshore outsourcing, is an invaluable addition to academic, research, and corporate libraries.
Knowledge discovery tools and techniques are used in an increasing number of scientific and commercial areas for the analysis
of large data sets. When large data repositories are coupled with geographic distribution of data, users and systems, it is
necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On
the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing.
In this paper we introduce a software architecture for parallel and distributed knowledge discovery (PDKD) systems that is
built on top of computational grid services that provide dependable, consistent, and pervasive access to high-end computational
resources. The proposed architecture uses the grid services and defines a set of additional layers to implement the services
of distributed knowledge discovery process on grid-connected sequential or parallel computers.
Collaborating centers in time zones six to eight hours apart can transfer work so that every center is working during the daytime. Although this concept avoids the hazards of night work, it requires careful planning and a way to automatically capture evolving knowledge.
Intelligent conversational channel (ICC) is a community channel developed to facilitate knowledge sharing activities by utilizing multiple agents to create virtual community. The concept of social knowledge is emphasized as the major source of knowledge to be shared among communities. The social knowledge is extracted not only from the community talks but also from scientific documents. We show the architecture of the system to do this and methodology for social knowledge extraction. Agents are used as the communicator to the community members to deliver the knowledge in a conversational manner.
Banks receive a wide variety of telex communications. Bank operators must sort these telexes and route them to the appropriate department for processing. Although certain messages can easily be classified and routed, others require a more thorough understanding of the telex content and bank organization to determine the proper destination. The large number of messages that must be reviewed each day, the urgency of these messages, and the difficulty of maintaining a staff of sufficiently skilled operators all indicate the advantages of automating this task. Thus, Prism is a system that combines case-based and inductive techniques to classify and route bank telexes. Developed by Cognitive Systems, Inc. (CSI), the Prism system has been in continual daily operation at Chase Manhattan Bank's Letter of Credit Department (Chase L/C) since October 1989 and has been customized for installation at Manufacturer's Hanover Trust (MHT) and the American Express Bank, Limited (AEBL).
This article was published in the journal, Journal of Information Science [© Sage]. This paper provides an overview of virtual teams in the information age, focussing on the definition of virtual teams, their salient characteristics, the communication issues they face, (including information overload, geographic and social distance), the technical issues involved (linking this to theories of media use), the issues raised by cultural diversity in the teams (including identity, trust and conflict) and managerial implications. Suggestions are made on how to address the issues raised and omissions from pervious research are highlighted.
This paper describes a Grid-aware image reviewing system (GridIMAGE) that allows practitioners to (a) select images from multiple geographically distributed digital imaging and communication in medicine (DICOM) servers, (b) send those images to a specified group of human readers and computer-assisted detection (CAD) algorithms, and (c) obtain and compare interpretations from human readers and CAD algorithms. The currently implemented system was developed using the National Cancer Institute caGrid infrastructure and is designed to support the identification of lung nodules on thoracic computed tomography. However, the infrastructure is general and can support any type of distributed review. caGrid data and analytical services are used to link DICOM image databases and CAD systems and to interact with human readers. Moreover, the service-oriented and distributed structure of the GridIMAGE framework enables a flexible system, which can be deployed in an institution (linking multiple DICOM servers and CAD algorithms) and in a Grid environment (linking the resources of collaborating research groups). GridIMAGE provides a framework that allows practitioners to obtain interpretations from one or more human readers or CAD algorithms. It also provides a mechanism to allow cooperative imaging groups to systematically perform image interpretation tasks associated with research protocols.
Just as the Internet is shifting its focus from information and communication to a knowledge delivery infrastructure, we see the Grid moving from computation and data management to a pervasive, worldwide knowledge management infrastructure. We have the technology to store and access data, but we seem to lack the ability to transform data tombs into useful data and extract knowledge from them. We review some of the current and future technologies that will impact the architecture, computational model, and applications of future grids. We attempt to forecast the evolution of computational grids into what we call the next-generation grid, with a particular focus on the use of semantics and knowledge discovery techniques and services. We propose a comprehensive software architecture for the next-generation grid, which integrates currently available services and components in Semantic Web, Semantic Grid, P2P, and ubiquitous systems. We'll also discuss a case study that shows how some new technologies can improve grid applications.
This paper describes a hybrid system which integrates CBR with an incremental neural network. The proposed system makes retrieval process efficient and in the same time maintains a continuous learning process. The proposed case hierarchy contains two memory levels. At the lower one, cases are gathered into groups by similarity. The upper level contains prototypes, each of which representing one group of cases of the lower levels. This upper level memory is used as an indexing system during the retrieval phase. In section 2, incremental prototype-based neural networks are described, in section 3 the hybrid model using a prototype-based neural network to index the case base is described. In section 4, a comparative study of this model with some inductive approaches (C4.5 and ID5R) is made. 2 PROTOTYPE-BASED INCREMENTAL NEURAL NETWORKS
How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.
The future interconnection environment will be a platform-independent Virtual Grid consisting of requirements, roles and resources. With machine-understandable semantics, a resource can actively and dynamically cluster relevant resources to provide on-demand services by understanding requirements and functions each other. Versatile resources are encapsulated to provide services in the form of single semantic image by using the uniform resource model. A resource can intelligently assist people to accomplish complex tasks and solve problems by participating versatile resource flow cycles through virtual roles to use proper knowledge, information, and computing resources. From this Virtual Grid point of view, this paper conceptualizes the Social Grid, Semantic Resource Grid and Knowledge Grid, then points out the key research issues of the future interconnection environment.
Ikujiro Nonaka e Hirotaka Takeuchi establecen una vinculación del desempeño de las empresas japonesas con su capacidad para crear conocimiento y emplearlo en la producción de productos y tecnologías exitosas en el mercado. Los autores explican que hay dos tipos de conocimiento: el explícito, contenido en manuales y procedimientos, y el tácito, aprendido mediante la experiencia y comunicado, de manera indirecta, en forma de metáforas y analogías. Mientras los administradores estadounidenses se concentran en el conocimiento explícito, los japoneses lo hacen en el tácito y la clave de su éxito estriba en que han aprendido a convertir el conocimiento tácito en explícito. Finalmente, muestran que el mejor estilo administrativo para crear conocimiento es el que ellos denominan centro-arriba-abajo, en el que los gerentes de niveles intermedios son un puente entre los ideales de la alta dirección y la realidad caótica de los niveles inferiores.
To increase the quality of decision making in construction companies, organizational memory should be enhanced and utilized effectively. Experiences of other companies should constitute an important part of organizational memory so that a construction company may have the chance to learn from the experiences of others and modify its behavior in the light of acquired knowledge. Within this study, a case-based reasoning (CBR) decision support tool is constructed to demonstrate how experiences of competitors in international markets may be used by contractors, to support international market selection decisions. 215 cases from the Turkish construction industry have been used to build the model, namely CBR-INT. The reliability of CBR-INT in predicting potential profitability of international projects and the level of competitiveness of Turkish contractors is around 90%. Moreover, CBR-INT has proven to be an effective tool for practitioners due to its high explanation capability and ease of use. Using the conceptual framework of CBR-INT, different CBR models can also be constructed for other countries.
Since contractors' bidding behaviors are affected by numerous factors related both to the specific features of the project and dynamically changed situations, bidding decision problems are highly unstructured. No clear rules can be found in delivering a bidding decision. In this problem domain, decisions are commonly made based upon intuition and past experience. Case-based reasoning (CBR) is a subbranch of artificial intelligence. It solves new problems by matching against similar problems that have been encountered and resolved in the past. It is a useful tool in dealing with complex and unstructured problems, which are difficult if not impossible to be theoretically modeled. This paper presents a case-based reasoning bidding system that helps contractors with the dynamic information varying with the specific features of the job and the new situation. In this system, bid cases are represented by sets of attributes derived from a preliminary survey of several experienced bidders, focusing, respectively, on two reasoning subgoals: (1) Risk; and (2) competition. Through the system, similar cases can be retrieved to assess the possible level of competition and risk margin. A hypothetical example is explained and evaluated to demonstrate the feasibility of the method. The effectiveness of this system is tested by a Monte Carlo simulation in comparison to the conventional statistical method.
This paper examines cultural awareness in knowledge transfer to China. The concepts of guanxi and mianzi are fundamentally important in understanding cultural interactions in China. These concepts, generally analyzed at the personal level, are extended here to relationships between firms and with governmental bodies. Our findings suggest that foreign investors in China must be aware of these key concepts and must use their knowledge to establish better institutional connections with locally owned partners and government. Using these concepts to build trust lies at the heart of interactions with local stakeholders including employees, local partners and government officials. Government support and a shared mindset can only be secured when mutual trust is established. This has to be achieved by long-term engagement with the key actors.
This paper presents an approach to facilitate the generation of new product ideas. In this approach, a product is represented
by a vector, which involves a number of product attributes. These attributes are defined based on the user-centered design
(UCD) paradigm. That is, the context of use and interactions with users for the product is described by these attributes.
By the product representation, a product database can be established. For a benchmarking product, we use the case-based reasoning
(CBR) technique to retrieve those products, which are “sufficiently relevant” to the benchmarking one, from the database. The functions of the retrieved products are the candidate new ideas to be added
on the benchmarking product. These retrieved products are screened manually to identify creative and valuable ideas. A prototype
system of this approach has been implemented. Experiments show that the proposed approach outperforms the brainstorming technique,
which has been widely used in industry.
This paper proposes a regression case based reasoning (RCBR) which applies different weights to independent variables before finding similar cases. The traditional CBR model has focused on finding similar cases from a case base without considering the importance of independent variables. Thus, when extracting similar cases the traditional CBR has put same weights on each independent variable.The proposed regression CBR (RCBR) finds a relative importance of independent variables from the relationship between independent variables and a dependent variable using a regression analysis and puts relative weights using regression coefficients on independent variables. Then, it selects nearest neighbor or similar cases using weighted independent variables through the traditional CBR machine and updates weights dynamically for the next target case and again performs the traditional CBR machine.
This paper proposes a knowledge grid model for sharing and managing globally distributed knowledge resources. The model organizes knowledge in a three-dimensional knowledge space, and provides a knowledge grid operation language, KGOL. Internet users can use the KGOL to create their knowledge grids, to put knowledge to them, to edit knowledge, to partially or wholly open their grids to all or some particular grids, and to get the required knowledge from the open knowledge of all the knowledge grids. The model enables people to conveniently share knowledge with each other when they work on the Internet. A software platform based on the proposed model has been implemented and used for knowledge sharing in research teams.
This paper explores the use of information technology to support knowledge sharing within and between communities of practice. In so doing, it presents a case of a multi-national organization's efforts to implement an organizational knowledge management (KM) system. The case traces both the technological solutions and the KM strategy of the organization as it met with various challenges along a several year period of establishing KM as organizational practice. The study highlights several lessons, including the possibility of a flexible KM strategy, the necessity for multiple channels of knowledge sharing, the desirability of expanding communities of practice, and the evolution of the role played by information technology as KM strategies evolve.
Rule-based and case-based reasoning are two popular approaches used in intelligent systems. Rules usually represent general knowledge, whereas cases encompass knowledge accumulated from specific (specialized) situations. Each approach has advantages and disadvantages, which are proved to be complementary in a large degree. So, it is well-justified to combine rules and cases to produce effective hybrid approaches, surpassing the disadvantages of each component method. In this paper, we first present advantages and disadvantages of rule-based and case-based reasoning and show that they are complementary. We then discuss the deficiencies of existing categorization schemes for integrations of rule-based and case-based representations. To deal with those deficiencies, we introduce a new categorization scheme. Finally, we briefly present representative approaches for the final categories of our scheme.
Virtual teams are becoming a preferred mechanism for harnessing, integrating, and applying knowledge that is distributed across organizations and in pockets of collaborative networks. In this article we recognize that knowledge application, among the three phases of knowledge management, has received little research attention. Paradoxically, this phase contributes most to value creation. Extending communication theory, we identify four challenges to knowledge integration in virtual team environments: constraints on transactive memory, insufficient mutual understanding, failure in sharing and retaining contextual knowledge, and inflexibility of organizational ties. We then propose knowledge management system (KMS) approaches to meet these challenges. Finally, we identify promising avenues for future research in this area.
With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.
The Globus Toolkit (GT) has been developed since the late 1990s to support the development of service-oriented distributed computing applications and infrastructures. Core GT components address, within a common framework, fundamental issues relating to security, resource access, resource management, data movement, resource discovery, and so forth. These components enable a broader “Globus ecosystem” of tools and components that build on, or interoperate with, GT functionality to provide a wide range of useful application-level functions. These tools have in turn been used to develop a wide range of both “Grid” infrastructures and distributed applications. I summarize here the principal characteristics of the recent Web Services-based GT4 release, which provides significant improvements over previous releases in terms of robustness, performance, usability, documentation, standards compliance, and functionality. I also introduce the new “dev.globus” community development process, which allows a larger community to contribute to the development of Globus software.
233 p., ref. bib. : ref. et notes dissem. A probing and incisive analysis of the major world transformation from the Age of Capitalism to the Knowledge Society and how it will affect society, economics, business, and politics now and in the years ahead. In Post-Capitalist Society Peter Drucker describes how every few hundred years a sharp transformation has taken place and greatly affected society―its worldview, its basic values, its business and economics, and its social and political structure. According to Drucker, we are right in the middle of another time of radical change, from the Age of Capitalism and the Nation-State to a Knowledge Society and a Society of Organizations. The primary resource in the post-capitalist society will be knowledge and the leading social groups will be "knowledge workers." Looking backward and forward, Drucker discusses the Industrial Revolution, the Productivity Revolution, the Management Revolution, and the governance of corporations. He explains the new functions of organizations, the economics of knowledge, and productivity as a social and economic priority. He covers the transformation from Nation-State to Megastate, the new pluralism of political systems, and the needed government turnaround. Finally, Drucker details the knowledge issues and the role and use of knowledge in post-capitalist society. Divided into three parts―Society, Polity, and Knowledge―Post―Capitalist Society provides a searching look into the future as well as a vital analysis of the past, focusing on the challenges of the present transition period and how, if we can understand and respond to them, we can create a new future.
With the Resource Description Framework (RDF) and Web Ontology Language (OWL) - the languages that power the semantic Web - becoming standards and new technologies reaching maturity for embedding semantics in existing Web pages and querying RDF knowledge stores, something exciting is clearly happening in this area. Whereas the research community is widely exploiting the AI technologies that motivate, in particular, the OWL DL sublanguage, the languages' more "Webby" features - sometimes referred to as the "dark side" of the semantic Web - are powering the Web 3.0 technology space
PS3 doubles folding@home's processing power
- E Huang
Connectionistsymbolic integration
- F Alexandre