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Semantic similarity based on corpus statistics and lexical taxonomy

by Jay J. Jiang, David W. Conrath - Proc of 10th International Conference on Research in Computational Linguistics, ROCLING’97 , 1997
"... This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantifie ..."
Abstract - Cited by 873 (0 self) - Add to MetaCart
quantified with the computational evidence derived from a distributional analysis of corpus data. Specifically, the proposed measure is a combined approach that inherits the edge-based approach of the edge counting scheme, which is then enhanced by the node-based approach of the information content

Maximum entropy markov models for information extraction and segmentation

by Andrew McCallum, Dayne Freitag, Fernando Pereira , 2000
"... Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial ..."
Abstract - Cited by 561 (18 self) - Add to MetaCart
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled

A New Location Technique for the Active Office

by Andy Ward, Alan Jones , 1997
"... Configuration of the computing and communications systems found at home and in the workplace is a complex task that currently requires the attention of the user. Recently, researchers have begun to examine computers that would autonomously change their functionality based on observations of who or ..."
Abstract - Cited by 515 (4 self) - Add to MetaCart
Configuration of the computing and communications systems found at home and in the workplace is a complex task that currently requires the attention of the user. Recently, researchers have begun to examine computers that would autonomously change their functionality based on observations of who

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 549 (5 self) - Add to MetaCart
is essential. (iv) Relearning after damage is much faster than learning during the original training. (v) Distributed or spaced practice is more effective for long-term retention than massed practice. Network models can be constructed that have the same performance and learning characteristics on a particular

Hypertext Transfer Protocol - HTTP/1.1

by R. Fielding, H. Frystyk, Tim Berners-Lee, J. Gettys, J. C. Mogul , 1996
"... The Hypertext Transfer Protocol (HTTP) is an application-level protocol for distributed, collaborative, hypermedia information systems. It is a generic, stateless, object-oriented protocol which can be used for many tasks, such as name servers and distributed object management systems, through exten ..."
Abstract - Cited by 908 (27 self) - Add to MetaCart
The Hypertext Transfer Protocol (HTTP) is an application-level protocol for distributed, collaborative, hypermedia information systems. It is a generic, stateless, object-oriented protocol which can be used for many tasks, such as name servers and distributed object management systems, through

Solving multiclass learning problems via error-correcting output codes

by Thomas G. Dietterich, Ghulum Bakiri - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH , 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
Abstract - Cited by 726 (8 self) - Add to MetaCart
of multiclass learning tasks. We also demonstrate that this approach is robust with respect to changes in the size of the training sample, the assignment of distributed representations to particular classes, and the application of over tting avoidance techniques such as decision-tree pruning. Finally,we show

The Skill Content of Recent Technological Change: An Empirical Exploration

by David H. Autor, Frank Levy, Richard J. Murnane , 2000
"... Recent empirical and case study evidence documents a strong association between the adoption of computers and increased use of college educated or non-production workers. With few exceptions, the conceptual link explaining how computer technology complements skilled labor or substitutes for unskille ..."
Abstract - Cited by 643 (28 self) - Add to MetaCart
of our framework is that, to a first approximation, computer capital substitutes for a limited and well-defined set of human activities, those involving repetitive information processing (cognitive) and routine manual tasks. This observation leads to a set of hypotheses that we test using samples

The Aurora Experimental Framework for the Performance Evaluation of Speech Recognition Systems under Noisy Conditions

by David Pearce, Hans-günter Hirsch, Ericsson Eurolab Deutschland Gmbh - in ISCA ITRW ASR2000 , 2000
"... This paper describes a database designed to evaluate the performance of speech recognition algorithms in noisy conditions. The database may either be used to measure frontend feature extraction algorithms, using a defined HMM recognition back-end, or complete recognition systems. The source speech f ..."
Abstract - Cited by 534 (6 self) - Add to MetaCart
for this database is the TIdigits, consisting of connected digits task spoken by American English talkers (downsampled to 8kHz). A selection of 8 different real-world noises have been added to the speech over a range of signal to noise ratios with controlled filtering of the speech and noise. The framework

Instance-based learning algorithms

by David W. Aha, Dennis Kibler, Marc K. Albert - Machine Learning , 1991
"... Abstract. Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms that learn decision trees, classification rules, and distributed networks. However, no investigation has analyzed algorithms that use only specific instances to ..."
Abstract - Cited by 1389 (18 self) - Add to MetaCart
Abstract. Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms that learn decision trees, classification rules, and distributed networks. However, no investigation has analyzed algorithms that use only specific instances

Real-Time Obstacle Avoidance for Manipulators and Mobile Robots

by Oussama Khatib - INT. JOUR OF ROBOTIC RESEARCH , 1986
"... This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi-tionally considered a high level planning problem, can be effectively distributed between different levels of control, al- ..."
Abstract - Cited by 1345 (28 self) - Add to MetaCart
This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi-tionally considered a high level planning problem, can be effectively distributed between different levels of control, al
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