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Ripple-down Rules
Ripple-down rules (RDR) are a way of approaching knowledge acquisition. Knowledge acquisition refers to the transfer of knowledge from human experts to knowledge-based systems. Introductory material Ripple-down rules are an incremental approach to knowledge acquisition and covers a family of techniques. RDR were proposed by Compton and Jansen based on experience maintaining the expert system GARVAN-ES1 (Compton and Jansen 1988). The original GARVAN-ES1 (Horn et al. 1985) employed a knowledge acquisition process, based on Test Driven Development, where new cases that were poorly classified by the system were added to a data base and then used to incrementally refine the knowledge base. The added cases, whose conclusions conflicted with the advice of the system were termed "cornerstone cases". Consequently, the data base grew iteratively with each refinement to the knowledge. The data base could then be used to test changes to the knowledge. Knowledge acquisition tools, similar to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Acquisition
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and frame-based ontologies. Expert systems were one of the first successful applications of artificial intelligence technology to real world business problems. Researchers at Stanford and other AI laboratories worked with doctors and other highly skilled experts to develop systems that could automate complex tasks such as medical diagnosis. Until this point computers had mostly been used to automate highly data intensive tasks but not for complex reasoning. Technologies such as inference engines allowed developers for the first time to tackle more complex problems. As expert systems scaled up from demonstration prototypes to indust ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge-based Systems
A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. Knowledge-based systems were the focus of early artificial intelligence researchers in the 1980s. The term can refer to a broad range of systems. However, all knowledge-based systems have two defining components: an attempt to represent knowledge explicitly, called a knowledge base, and a reasoning system that allows them to derive new knowledge, known as an inference engine. Components The knowledge base contains domain-specific facts and rules about a problem domain (rather than knowledge implicitly embedded in procedural code, as in a conventional computer program). In addition, the knowledge may be structured by means of a subsumption ontology, frames, conceptual graph, or logical assertions. The inference engine uses general-purpose reasoning methods to infer new knowledge and to solve problems in the problem domain. Most commonly, it employs forw ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Paul Justin Compton
Paul Compton (born 1944) is an Emeritus Professor at the University of New South Wales (UNSW). He was also the former Head of the UNSW School of Computer Science and Engineering. He is known for proposing "ripple-down rules". Career Paul Compton worked at the Garvan Institute before his appointment at UNSW. He was the Head of School from 1996 to 1998, and again from 2003 to 2010. He was very popular as Head of School, and upon his retirement a large gathering fare-welled him, as well as creating a YouTube slide-show tribute. Research Paul Compton along with R. Jansen proposed "ripple-down rules Ripple-down rules (RDR) are a way of approaching knowledge acquisition. Knowledge acquisition refers to the transfer of knowledge from human experts to knowledge-based systems. Introductory material Ripple-down rules are an incremental approach ..." in 1988.P. Compton and R. Jansen (1988). "Knowledge in Context: a strategy for expert system maintenance". Proc. Second Australian Jo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Tree
A decision tree is a decision support system, decision support recursive partitioning structure that uses a Tree (graph theory), tree-like Causal model, model of decisions and their possible consequences, including probability, chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in Decision tree learning, machine learning. Overview A decision tree is a flowchart-like structure in which each internal node represents a test on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules. In decision analysis, a de ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Java (programming Language)
Java is a High-level programming language, high-level, General-purpose programming language, general-purpose, Memory safety, memory-safe, object-oriented programming, object-oriented programming language. It is intended to let programmers ''write once, run anywhere'' (Write once, run anywhere, WORA), meaning that compiler, compiled Java code can run on all platforms that support Java without the need to recompile. Java applications are typically compiled to Java bytecode, bytecode that can run on any Java virtual machine (JVM) regardless of the underlying computer architecture. The syntax (programming languages), syntax of Java is similar to C (programming language), C and C++, but has fewer low-level programming language, low-level facilities than either of them. The Java runtime provides dynamic capabilities (such as Reflective programming, reflection and runtime code modification) that are typically not available in traditional compiled languages. Java gained popularity sh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Weka (machine Learning)
The weka, also known as the Māori hen or woodhen (''Gallirallus australis'') is a flightless bird species of the rail family. It is endemic to New Zealand. Some authorities consider it as the only extant member of the genus '' Gallirallus''. Four subspecies are recognized but only two (northern/southern) are supported by genetic evidence. The weka are sturdy brown birds about the size of a chicken. As omnivores, they feed mainly on invertebrates and fruit. Weka usually lay eggs between August and January; both sexes help to incubate. Description Weka are large rails. They are predominantly rich brown mottled with black and grey; the brown shade varies from pale to dark depending on subspecies. The male is the larger sex at in length and in weight. Females measure in length and weigh . The reduced wingspan ranges from . The relatively large, reddish-brown beak is about long, stout and tapered, and used as a weapon. The pointed tail is near-constantly being flicked, a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Case-based Reasoning
Case-based reasoning (CBR), broadly construed, is the process of solving new problems based on the solutions of similar past problems. In everyday life, an auto mechanic who fixes an engine by recalling another car that exhibited similar symptoms is using case-based reasoning. A lawyer who advocates a particular outcome in a trial based on legal precedents or a judge who creates case law is using case-based reasoning. So, too, an engineer copying working elements of nature (practicing biomimicry) is treating nature as a database of solutions to problems. Case-based reasoning is a prominent type of analogy solution making. It has been argued that case-based reasoning is not only a powerful method for computer reasoning, but also a pervasive behavior in everyday human problem solving; or, more radically, that all reasoning is based on past cases personally experienced. This view is related to prototype theory, which is most deeply explored in cognitive science. Process Case ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Trees
A decision tree is a decision support system, decision support recursive partitioning structure that uses a Tree (graph theory), tree-like Causal model, model of decisions and their possible consequences, including probability, chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in Decision tree learning, machine learning. Overview A decision tree is a flowchart-like structure in which each internal node represents a test on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules. In decision analysis, a de ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multiple-classification Ripple-down Rules
Multiple-classification ripple-down rules (MCRDR) is an incremental knowledge acquisition technique which preserves the benefits and essential strategy of ripple-down rules (RDR) in handling the multiple classifications. MCRDR, the extension of RDR, is based on the assumption that the knowledge an expert provides is essentially a justification for a conclusion in a particular context. Implementations Below is a list of implementations of MCRDR * The alpha version of RDR(MCRDR) Framework was developed by UNSW and UTAS Research Team and funded by ARC (System available aBESTRDR * RDR(MCRDR) document classifier was developed by Dr.Yang Sok Kim and AProf.Byeong Ho Kang (System available aBESTRDR * RDR(MCRDR) smart expert system was developed by UTAS Research Team and funded by Hyundai Steel. * Pacific Knowledge Systems (PKS) uses a commercial product called RippleDown Expert that is based on Multiple Classification Ripple Down Rules Medscope Medication Review Mentoruses Multiple Classi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Management
Knowledge management (KM) is the set of procedures for producing, disseminating, utilizing, and overseeing an organization's knowledge and data. It alludes to a multidisciplinary strategy that maximizes knowledge utilization to accomplish organizational goals. Courses in business administration, information systems, management, libraries, and information science are all part of knowledge management, a discipline that has been around since 1991. Information and media, computer science, public health, and public policy are some of the other disciplines that may contribute to KM research. Numerous academic institutions provide master's degrees specifically focused on knowledge management. As a component of their IT, human resource management, or business strategy departments, many large corporations, government agencies, and nonprofit organizations have resources devoted to internal knowledge management initiatives. These organizations receive KM guidance from a number of consulting ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
