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Topic: Knowledge Machine

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Seymour Papert

Artificial intelligence

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	Machine translation - Wikipedia, the free encyclopedia
		Machine translation (MT) is a form of translation where a computer program analyses the text in one language — the "source text" — and then attempts to produce another, equivalent text in another language — the target text — without human intervention.
		Machine translation can use a method based on linguistic rules, which means that words will be translated in a linguistic way — the most suitable (orally speaking) words of the target language will replace the ones in the source language.
		In machine translation, the translator supports the machine, that is to say that the computer or program translates the text, which is then edited by the translator, whereas in computer-assisted translation, the computer program supports the translator, who translates the text himself, making all the essential decisions involved.
	en.wikipedia.org /wiki/Machine_translation (1437 words)

	A Concept Map-Based Knowledge Modeling Approach to Expert Knowledge Sharing
		Knowledge models of this sort contain content that is different from the more general information in typical reference material and that is organized quite differently than standard (sequential) textbook knowledge or mainstream hypermedia learning systems.
		These knowledge models tend to be large and complex (reflecting the complexity of real domains of knowledge) with interwoven themes and rich interconnections of the concepts based on the expert's highly articulated mental model of the domain.
		As this and other knowledge modeling projects have proceeded, it has become evident that the "real" expertise is not in the documents, texts, or even the procedural handbooks that the experts use, but rather in bits and pieces of these, organized to support the heuristic knowledge elicited to tie them all together.
	www.ihmc.us /users/acanas/Publications/IKS2002/IKS.htm (3304 words)

	Introducing a new kind of publishing: The Electronic Knowledge Publishing
		Knowledge, as we believe, is a basis of an ability of man to understand what is going and to act effectively in accordance with a situation.
		Individual knowledge is an internal matter for a person, so no one needs, as a rule, to present this knowledge in external form for himself, such as text, picture etc. Sometime people use external objects to activate their knowledge, but as we think, if they have no knowledge inside already, nothing can be activated.
		Thus there were appeared external presentations of knowledge such as speech, texts, pictures etc. Primarily a speech and derived from speech text, that is a pictorial presentation of speech, are main modes of external presentation of knowledge.
	www.geocities.com /gkmgeosite/gkmekp.htm (5269 words)

	Emerging Technologies Artificial Intelligence Machine Learning
		Machine Learning, Part I: Types of Learning Problems (aihorizon)- Before launching into a series of tutorials on different machine learning algorithms, it can be helpful to understand the background material--what each algorithm is aiming to do, and where it fits into the world of artificial intelligence.
		Machine Learning, Part III: Testing Algorithms, and The "No Free Lunch Theorem" (aihorizon)- Now that you have a sense of the classifications of machine learning algorithms, before diving into the specifics of individual algorithms, the only other background required is a sense of how to test machine learning algorithms.
		Machine Learning and Inference Laboratory - This research lab conducts fundamental and experimental research on the development of intelligent systems capable of advanced forms of learning, inference, and knowledge generation, and applies them to real-world problems.
	emergingtechnologies.ittoolbox.com /topics/t.asp?t=310&p=317&h2=317&h1=310 (835 words)

	Cutting Pasta by Machine
		Hand-cranked machines are easier to clean because the dough is drier and is feed into the machine as a solid mass compared to the electric machine whose dough has a loose consistency.
		The hand-cranked extrusion machine is slightly harder to clean than the cutting machine because the dies require a little additional work to clean.
		The hand-cranked machine requires room to mix the dough, to knead and roll the dough, an area to lay the rolled pasta sheets before cutting, an area for the machine and a place to lay the finished pasta out on a floured surface.
	www.hormel.com /templates/knowledge/knowledge.asp?catitemid=44&id=524 (1588 words)

	Machine Learning for Information Retrieval: Neural Networks, Symbolic Learning, and Genetic Algorithms
		Knowledge engineers or system designers need to be able to identify subject and classification knowledge from some sources (usually some domain experts) and to represent the knowledge in computer systems.
		Knowledge and information can be stored in single-layered interconnected neurons (nodes) and weighted synapses (links) and can be retrieved based on the network's parallel relaxation method - nodes are activated in parallel and are traversed until the network reaches a stable state (convergence).
		We feel that the proper selection of knowledge representation and the adaptation of machine learning algorithms in the IR context are essential to the successful use of such techniques.
	ai.bpa.arizona.edu /papers/mlir93/mlir93.html (12851 words)

	Reports
		Not surprisingly, however, generating this knowledge for new domains is time-consuming, difficult, and error-prone, and requires the expertise of computational linguists familiar with the underlying NLP system.
		Machine learning techniques for inductive learning have also become increasingly available and offer powerful mechanisms for simplifying the knowledge acquisition process.
		The objective of this research is to address this knowledge engineering bottleneck for natural language processing (NLP) systems by developing algorithms that use inductive learning techniques to allow NLP systems to bootstrap their own knowledge bases directly from text.
	nsf-workshop.engr.ucf.edu /papers/Cardie.asp (1172 words)

	Machine Learning
		The notes concentrate on the important ideas in machine learning---it is neither a handbook of practice nor a compendium of theoretical proofs.
		In response to the difficulties of encoding ever-increasing volumes of knowledge in modern AI systems, many researchers have recently turned their attention to machine learning as a means to overcome the knowledge acquisition bottleneck.
		Machine learning of grammars finds a variety of applications in syntactic pattern recognition, adaptive intelligent agents, diagnosis, computational biology, systems modelling, prediction, natural language acquisition, data mining and knowledge discovery.
	www.aaai.org /AITopics/html/machine.html (2951 words)

	Embedding Machine learning & Knowledge Acquisition (Site not responding. Last check: 2007-10-11)
		Machine learning is concerned with developing algorithms capable of discovering new relationships -- expressed as rules -- between concepts in a given KB.
		In the context of KBS, these activities can also be viewed as forms of automatic analysis of existing knowledge, resulting in novel interpretations of existing data and/or the discovery of new relationships and structures in initially unstructured data [Sommer1995c].
		Early work in ML was not concerned with this embedded aspect of learning algorithms, but rather with ``pure'' algorithms that take input and produce a result (a concept or rule) not necessarily expressed in the same language as the input, and not interpreted in any way by the algorithm itself (one-shot learning).
	www.geocities.com /ResearchTriangle/Node/1499/node4.html (486 words)

	Glossary of Terms Journal of Machine Learning
		This step usually precedes the machine learning step, although the knowledge discovery process may indicate that further cleaning is desired and may suggest ways to improve the quality of the data.
		In most machine learning work, instances are described by feature vectors; some work uses more complex representations (e.g., containing relations between instances or between parts of instances).
		In Knowledge Discovery, machine learning is most commonly used to mean the application of induction algorithms, which is one step in the knowledge discovery process.
	ai.stanford.edu /~ronnyk/glossary.html (1094 words)

	The Children's Machine by Seymour Papert
		Knowledge is transmitted "through a pipeline from teacher to student" and is "treated like money, to be put away in a bank for the future".
		He imagines a machine he refers to as "The Knowledge Machine" which would allow children a rich exploration of the world.
		Whether or not Papert's Knowledge Machine or his little schools become a reality will constitute less of an imperative in terms of change than will our ability to reconceptualize learning.
	www.cdli.ca /~elmurphy/emurphy/papert.html (913 words)

	Gazelle/Japangloss
		One of the major bottlenecks in the construction of modern Machine Translation (MT) systems is the expense of acquiring large enough lexicons, grammars, collections of rules, etc., for the system to handle unrestricted input.
		Generally, statistical techniques and statistically gathered knowledge provide large-scale coverage at a lower level of quality, while symbolic (linguistic and other traditional) techniques provide reduced coverage of the language but at higher levels of quality.
		We summarize recent machine translation (MT) research at the Information Sciences Institute of USC, and we describe its application to the development of a Japanese-English newspaper MT system.
	www.isi.edu /natural-language/mt/japangloss-old.html (1483 words)

	PC AI - Machine Learning
		Overview: Machine learning is the subfield of AI that studies the automated acquisition of domain-specific knowledge.
		Machine learning can be looked at as a framework for doing AI research and development.
		Five main areas of machine learning are: analytic learning methods; neural network (connectionist) learning methods; genetic algorithms and classifier systems; empirical methods for inducing rules and decision trees; and case-based approaches to learning.
	www.pcai.com /web/ai_info/machine_learning.html (1021 words)

	Knowledge Machine - Wikipedia, the free encyclopedia
		The Knowledge Machine is a concept of Seymour Papert, which is intended to enable children to explore any situation and engage them completely.
		Although Papert never clearly defined the Knowledge Machine, one interpretation is a virtual reality device that allows the user to slip into any situation and have a simulated experience of that situation.
		This article relating to education is a stub.
	en.wikipedia.org /wiki/Knowledge_Machine (89 words)

	Knowledge Acquisition with a Knowledge-Intensive Machine Learning System - Brunk, Pazzani (ResearchIndex) (Site not responding. Last check: 2007-10-11)
		We argue that existing machine learning techniques can be made more useful as knowledge acquisition tools by allowing the expert to have greater control over and interaction with the learning process.
		We describe a number of extensions to FOCL (a multistrategy Horn-clause learning program) that have greatly enhanced its power as a knowledge acquisition tool, paying particular attention to the...
		Knowledge acquisition with a knowledgeintensive machine learning system, 1992.
	citeseer.ist.psu.edu /100742.html (489 words)

	Knowledge Machine
		The great appeal of science fiction comes from the fact that it forms an uninhibited forum for developing the vision of the future society; a vision that is free of peer pressure, peer review and the debilitating compliance with the publish-or-perish principle.
		Though the overall progress in artificial intelligence seems to be far from the point envisioned in the super-brain fiction, a different sort of tools and techniques creep into place with a potential to change the world as we know it; still with human factor playing the central role.
		I hope that I earlier succeeded in demonstrating that the concept of Knowledge Machine will gain greatly on its attractiveness by adapting to the known properties of human memory and cognition.
	www.supermemo.com /english/ol/knowmachine.htm (1956 words)

	Psychology and the Scientific Method (Site not responding. Last check: 2007-10-11)
		Psychology is defined as the application of the scientific method to develop knowledge about behavior and mental processes.
		The first psychology lab was established in Germany in 1879 and performed pure or basic research, knowledge for the sake of knowledge.
		They are interested in gaining knowledge that affects large groups of people known as populations, but due to limited resources, they work with smaller groups known as samples and generalize their findings to the population.
	www.viterbo.edu /personalpages/faculty/DWILLMAN/p230/sci_meth.htm (319 words)

	The KANT Project Home Page
		The KANT project, part of the Center for Machine Translation (CMT) at Carnegie Mellon University (CMU), was founded in 1989 for the research and development of large-scale, practical translation systems for technical documentation.
		KANT uses a controlled vocabulary and grammar for each source language, and explicit yet focused semantic models for each technical domain to achieve very high accuracy in translation.
		The KANTOO (kahn'-toe) project is an object-oriented C++ implementation of KANT technology for machine translation.
	www.lti.cs.cmu.edu /Research/Kant (506 words)

	[No title]
		Electronic knowledge systems are based on human knowledge found in external sources and really multiply human intellectual abilities with facilities for effective immediate consulting.
		General Knowledge Machine is a set of tools, dedicated to effective knowledge search, on-line knowledge-based consulting and adaptive learning.
		General Knowledge Machine e-knowledge base engine ('soz.exe' and 'gkm.exe') is written in GNU Fortran compiler.
	gkm-ekp.sourceforge.net /gkm-author-guide.html (2119 words)

	Children of the Machine (Site not responding. Last check: 2007-10-11)
		The real question about the Knowledge Machine -- as also about television -- is whether the expectations it induces, and the experience it offers, have anything to do with a healthy, knowledge- producing participation in the world.
		To lose sight of the child's healthy dependence upon the teacher is to forget that all knowledge is knowledge of the human being.
		And he suggests that schools may soon have no choice in the matter, for the explorers of the Knowledge Machine "will be even less likely than the players of video games to sit quietly through anything even vaguely resembling the elementary- school curriculum as we have known it up to now!" (p.
	www.praxagora.com /~stevet/fdnc/ch14.html (8402 words)

	[No title]
		MACHINE TRANSLATION For aims and scope, submission of papers information and ordering information, see file coat.inf.
		Knowledge systems and Prolog: a logical approach to expert systems and natural language processing K. van der Wilt - C. Roads (ed.).
		From syntax to semantics: insights from machine translation R. Gebruers - C.V. Cernov (ed.).
	www.cs.cmu.edu /Groups/AI/pubs/publishers/Kluwer/journals/coat.toc (858 words)

	Machine Learning, Knowledge Acquisition & Refinement Research at Aberdeen
		In an information society, it is essential to possess, or to be able to access, knowledge in order to make sense of information, function efficiently, and provide good products and good service.
		Yet there are fundamental problems associated with the management of knowledge (capturing, representing, and distributing knowledge) that for too long have been addressed in isolation.
		Knowledge refinement and repair in a multi-agent context.
	www.csd.abdn.ac.uk /~pedwards/MLNet (1475 words)

	EPSY 5240 (Site not responding. Last check: 2007-10-11)
		Papert believes that we could create a "Knowledge Machine" whereby children could have a wealth of information at their fingertips by using speech, touch, or gestures.
		This sort of machine would allow children to explore a world significantly richer than that which is currently offered through printed books.
		The Knowledge Machine would offer children a chance to do that, even those who may be considered educationally "illiterate".
	carbon.cudenver.edu /public/education/edschool/cog/bibs/pat2.html (418 words)

	General Knowledge Machine Research Group
		It is intended to provide transformation of individual knowledge into knowledge publicly accessible and usable for immediate consulting and adaptive learning.
		History: General Knowledge Machine Research Group was founded in 1986 as informal non-profit institution by mathematicians and IT experts.
		It means that in reality significant part of knowledge is not used by anyone, and many problems are not solved because no one learns needed knowledge.
	gkm-ekp.sourceforge.net (1023 words)

	MLnet OiS - Find information and resources on Machine Learning, Knowledge Discovery, Data Mining, Case-based Reasoning, ... (Site not responding. Last check: 2007-10-11)
		This site is dedicated to the field of machine learning, knowledge discovery, case-based reasoning, knowledge acquisition, and data mining.
		And of course, we greatly appreciate any kind of feedback, so send us your comments and suggestions.
		As you can see, we are working hard on making this site a major resource for machine learning, knowledge discovery, and data mining.
	www.mlnet.org (351 words)

	Open Directory - Computers: Artificial Intelligence: Machine Learning (Site not responding. Last check: 2007-10-11)
		Kernel machines - A central information source for the area of Support Vector Machines, Gaussian Process prediction, Mathematical Programming with Kernels, Regularization Networks, Reproducing Kernel Hilbert Spaces, and related methods.
		Machine learning for user modeling - Resources for researchers and practitioners interested in the use of learning techniques in intelligent, user-adaptive systems.
		Machine Learning in Games - How computers can learn to get better at playing games.
	dmoz.org /Computers/Artificial_Intelligence/Machine_Learning (524 words)

	Knowledge Machine Drives DC (Site not responding. Last check: 2007-10-11)
		Knowledge Machine Drives DC Recently I read the story about GW’s economic effects on DC (“Measuring GW’s Economic Impact on the Metro Area,” ByGeorge!
		The unique effect of a great university on the economic development of a large city is through the externalities created by the preservation, dissemination and enhancement of research and technological development.
		The University faculty have organized themselves as a unique “knowledge machine” that is open to the public in ways that other research institutions cannot duplicate.
	www.gwu.edu /~bygeorge/081704/econletter.html (273 words)

	FPuX - Soda Machine Knowledge (Site not responding. Last check: 2007-10-11)
		I never knew stuff like this was still possible with modern soda machines.
		Although I have neither the size nor the desire to steal free soda, I may have to try out the debug mode mentioned at the end of the article.
		The article seems to be slanted towards Pepsi machines, not sure if similar things apply to Coke or other varieties.
	fpux.com /Blog/Righteous_Hacks/Soda_Machine_Knowledge.html (81 words)

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