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The Symbol Grounding Problem

by Stevan Harnad , 1990
"... There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the "symbol grounding problem": How can the semantic interpretation of a formal symbol system be m ..."
Abstract - Cited by 1072 (18 self) - Add to MetaCart
be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their (arbitrary) shapes, be grounded in anything but other meaningless symbols? The problem is analogous to trying to learn

Designing Learning

by Ann C. Baker, Patricia J. Jensen, David A. Kolb, D. A. Conversational, Ann Baker, Patricia Jensen, David Kolb - In , 2004
"... …Truth [is] being involved in an eternal conversation about things that matter, conducted with passion and discipline…truth is not in the conclusions so much as in the process of conversation itself…if you want to be in truth you must be in conversation. Parker Palmer ..."
Abstract - Cited by 555 (9 self) - Add to MetaCart
…Truth [is] being involved in an eternal conversation about things that matter, conducted with passion and discipline…truth is not in the conclusions so much as in the process of conversation itself…if you want to be in truth you must be in conversation. Parker Palmer

Inductive Learning Algorithms and Representations for Text Categorization

by Susan Dumais, John Platt, Mehran Sahami, David Heckerman , 1998
"... Text categorization – the assignment of natural language texts to one or more predefined categories based on their content – is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text categori ..."
Abstract - Cited by 641 (8 self) - Add to MetaCart
categorization in terms of learning speed, realtime classification speed, and classification accuracy. We also examine training set size, and alternative document representations. Very accurate text classifiers can be learned automatically from training examples. Linear Support Vector Machines (SVMs

Discovery of Grounded Theory

by Barney G. Glaser, Judith Holton , 1967
"... Abstract: This paper outlines my concerns with Qualitative Data Analysis ’ (QDA) numerous remodelings of Grounded Theory (GT) and the subsequent eroding impact. I cite several examples of the erosion and summarize essential elements of classic GT methodology. It is hoped that the article will clarif ..."
Abstract - Cited by 2485 (12 self) - Add to MetaCart
Abstract: This paper outlines my concerns with Qualitative Data Analysis ’ (QDA) numerous remodelings of Grounded Theory (GT) and the subsequent eroding impact. I cite several examples of the erosion and summarize essential elements of classic GT methodology. It is hoped that the article

Knowledge representations, reasoning and declarative problem solving . . .

by Chitta Baral , 2001
"... ..."
Abstract - Cited by 714 (43 self) - Add to MetaCart
Abstract not found

NewsWeeder: Learning to Filter Netnews

by Ken Lang - in Proceedings of the 12th International Machine Learning Conference (ML95 , 1995
"... A significant problem in many information filtering systems is the dependence on the user for the creation and maintenance of a user profile, which describes the user's interests. NewsWeeder is a netnews-filtering system that addresses this problem by letting the user rate his or her interest l ..."
Abstract - Cited by 555 (0 self) - Add to MetaCart
level for each article being read (1-5), and then learning a user profile based on these ratings. This paper describes how NewsWeeder accomplishes this task, and examines the alternative learning methods used. The results show that a learning algorithm based on the Minimum Description Length (MDL

Principled design of the modern web architecture

by Roy T. Fielding, Richard N. Taylor - ACM Trans. Internet Techn
"... The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia system. The modern Web architecture emphasizes scalability of component interactions, generality of interfaces, independent deployment of c ..."
Abstract - Cited by 507 (14 self) - Add to MetaCart
of components, and intermediary components to reduce interaction latency, enforce security, and encapsulate legacy systems. In this paper, we introduce the Representational State Transfer (REST) architectural style, developed as an abstract model of the Web architecture to guide our redesign and definition

A learning algorithm for Boltzmann machines

by H. Ackley, E. Hinton, J. Sejnowski - Cognitive Science , 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
Abstract - Cited by 586 (13 self) - Add to MetaCart
to a gen-eral learning rule for modifying the connection strengths so as to incorporate knowledge obout o task domain in on efficient way. We describe some simple examples in which the learning algorithm creates internal representations thot ore demonstrobly the most efficient way of using

Parallel Networks that Learn to Pronounce English Text

by Terrence J. Sejnowski, Charles R. Rosenberg - COMPLEX SYSTEMS , 1987
"... This paper describes NETtalk, a class of massively-parallel network systems that learn to convert English text to speech. The memory representations for pronunciations are learned by practice and are shared among many processing units. The performance of NETtalk has some similarities with observed h ..."
Abstract - Cited by 548 (5 self) - Add to MetaCart
This paper describes NETtalk, a class of massively-parallel network systems that learn to convert English text to speech. The memory representations for pronunciations are learned by practice and are shared among many processing units. The performance of NETtalk has some similarities with observed

Transductive Inference for Text Classification using Support Vector Machines

by Thorsten Joachims , 1999
"... This paper introduces Transductive Support Vector Machines (TSVMs) for text classification. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try to minimiz ..."
Abstract - Cited by 887 (4 self) - Add to MetaCart
This paper introduces Transductive Support Vector Machines (TSVMs) for text classification. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try
Results 1 - 10 of 634,905