Knowledge Base A knowledge base (KB) is a technology used to store complex structured and unstructured information used by a computer system. The initial use of the term was in connection with expert systems which were the first knowledge-based systems. The original use of the term knowledge-base was to describe one of the two sub-systems of a knowledge-based system. A knowledge-based system consists of a knowledge-base that represents facts about the world and an inference engine that can reason about those facts and use rules and other forms of logic to deduce new facts or highlight inconsistencies.[1] The term 'knowledge-base' was to distinguish from the more common widely used term database. At the time (the 1970s) virtually all large Management Information Systems stored their data in some type of hierarchical or relational database. Flat data. Early expert systems also had little need for multiple users or the complexity that comes with requiring transactional properties on data. See also[edit]
Knowledge-Based Systems Knowledge-Based systems were first developed by Artificial Intelligence researchers. These early knowledge-based systems were primarily expert systems. In fact the term is often used synonymously with expert systems. The difference is in the view taken to describe the system. Expert system refers to the type of task the system is trying to solve, to replace or aid a human expert in a complex task. Knowledge-based system refers to the architecture of the system, that it represents knowledge explicitly rather than as procedural code. The first knowledge-based systems were rule based expert systems. Acquisition & Maintenance. As knowledge-based systems became more complex the techniques used to represent the knowledge base became more sophisticated. Another advancement was the development of special purpose automated reasoning systems called classifiers. See also[edit] References[edit] External links[edit] Akerkar RA and Sajja Priti Srinivas (2009).
Knowledge Modeling Knowledge modeling is a process of creating a computer interpretable model of knowledge or standard specifications about a kind of process and/or about a kind of facility or product. The resulting knowledge model can only be computer interpretable when it is expressed in some knowledge representation language or data structure that enables the knowledge to be interpreted by software and to be stored in a database or data exchange file.Knowledge-based engineering or knowledge-aided design is a process of computer-aided usage of such knowledge models for the design of products, facilities or processes. The design of products or facilities then uses the knowledge model to guide the creation of the facility or product that need to be designed. In other words it used knowledge about a kind of object to create a product model of an (imaginary) individual object. Similarly, a knowledge model of a process is basically a specification of the sequence of process stages.
Legal Case Management The terms Legal case management (LCM) or matter management refer to a subset of law practice management and cover a range of approaches and technologies used by law firms and courts to leverage knowledge and methodologies for managing the life cycle of a case or matter more effectively.[1][2] Generally, the terms refer to the sophisticated information management and workflow practices that are tailored to meet the legal field's specific needs and requirements. As attorneys and law firms compete for clients they are routinely challenged to deliver services at lower costs with greater efficiency, thus firms develop practice-specific processes and utilize contemporary technologies to assist in meeting such challenges. Law practice management processes and technologies include case and matter management, time and billing, litigation support, research, communication and collaboration, data mining and modeling, and data security, storage, and archive accessibility. e-Discovery systems[edit]
Knowledge Sharing Knowledge Sharing is an activity through which knowledge (i.e., information, skills, or expertise) is exchanged among people, friends, families, communities (e.g., Wikipedia), or organizations.[1][2] Knowledge Flow[edit] Although knowledge is commonly treated as an object, Snowden has argued it is more appropriate to teach it as both a flow and a thing.[8] Knowledge as a flow can be related to the concept of tacit knowledge, discovered by Ludwik Hirszfeld[9] which was later further explicated by Nonaka.[10][11] While the difficulty of sharing knowledge is in transferring knowledge from one entity to another,[12][13] it may prove profitable for organizations to acknowledge the difficulties of knowledge transfer and its paradoxicality, adopting new knowledge management strategies accordingly.[8] Explicit Knowledge Sharing[edit] Tacit Knowledge Sharing[edit] Embedded Knowledge Sharing[edit] Importance of Knowledge Sharing in Organizations[edit] Challenges in Knowledge Sharing[edit] See also[edit]
Knowledge Transfer In organizational theory, knowledge transfer is the practical problem of transferring knowledge from one part of the organization to another. Like knowledge management, knowledge transfer seeks to organize, create, capture or distribute knowledge and ensure its availability for future users. It is considered to be more than just a communication problem. Background[edit] Argote & Ingram (2000) define knowledge transfer as "the process through which one unit (e.g., group, department, or division) is affected by the experience of another"[1] (p. 151). Szulanski's doctoral dissertation ("Exploring internal stickiness: Impediments to the transfer of best practice within the firm") proposed that knowledge transfer within a firm is inhibited by factors other than a lack of incentive. Knowledge transfer includes, but encompasses more than, technology transfer. Knowledge transfer between public and private domains[edit] Knowledge transfer in landscape ecology[edit] Types of knowledge[edit]
Knowledge Ecosystem The idea of a knowledge ecosystem is an approach to knowledge management which claims to foster the dynamic evolution of knowledge interactions between entities to improve decision-making and innovation through improved evolutionary networks of collaboration.[1][2] In contrast to purely directive management efforts that attempt either to manage or direct outcomes, knowledge ecosystems espouse that knowledge strategies should focus more on enabling self-organization in response to changing environments.[3] The suitability between knowledge and problems confronted defines the degree of "fitness" of a knowledge ecosystem. Articles discussing such ecological approaches typically incorporate elements of complex adaptive systems theory. Key Elements[edit] To understand knowledge ecology as a productive operation, it is helpful to focus on the knowledge ecosystem that lies at its core. Key elements of networked knowledge systems[6] include: 1. 2. 3. 4. See also[edit] Notes[edit] Clippinger, J.
Knowledge Community A knowledge community is community construct, stemming from the convergence of knowledge management as a field of study and social exchange theory. Formerly known as a discourse community and having evolved from forums and web forums, knowledge communities are now often referred to as a community of practice or virtual community of practice. As with any field of study, there are various points of view on the motivations, organizing principles and subsequent structure of knowledge communities. Perspectives[edit] As a web or virtual construct, knowledge communities can be said to have evolved from bulletin board systems, web forums and online discourse communities through the 80s and 90s. Stemming from social exchange theory, a well-established perspective is to view knowledge communities as a type of exchange. Knowledge communities can also be viewed as a method by which to do organizational or process innovation. Organizational behavior and structure[edit] Pitfalls[edit] References[edit]