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Results 1 - 10
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3,181
Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search
, 1996
"... Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning pr ..."
Abstract
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Cited by 579 (33 self)
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Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning
The Role of Emotion in Believable Agents
- Communications of the ACM
, 1994
"... Articial intelligence researchers attempting to create engaging apparently living creatures may nd important insight in the work of artists who have explored the idea of believable character In particular appropriately timed and clearly expressed emotion is a central requirement for believable ch ..."
Abstract
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Cited by 557 (1 self)
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Articial intelligence researchers attempting to create engaging apparently living creatures may nd important insight in the work of artists who have explored the idea of believable character In particular appropriately timed and clearly expressed emotion is a central requirement for believable
An extensive empirical study of feature selection metrics for text classification
- J. of Machine Learning Research
, 2003
"... Machine learning for text classification is the cornerstone of document categorization, news filtering, document routing, and personalization. In text domains, effective feature selection is essential to make the learning task efficient and more accurate. This paper presents an empirical comparison ..."
Abstract
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Cited by 496 (15 self)
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of twelve feature selection methods (e.g. Information Gain) evaluated on a benchmark of 229 text classification problem instances that were gathered from Reuters, TREC, OHSUMED, etc. The results are analyzed from multiple goal perspectives—accuracy, F-measure, precision, and recall—since each is appropriate
Loopy belief propagation for approximate inference: An empirical study. In:
- Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract
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Cited by 676 (15 self)
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Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon
Correlation-based feature selection for machine learning
, 1998
"... A central problem in machine learning is identifying a representative set of features from which to construct a classification model for a particular task. This thesis addresses the problem of feature selection for machine learning through a correlation based approach. The central hypothesis is that ..."
Abstract
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Cited by 318 (3 self)
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this evaluation formula with an appropriate correlation measure and a heuristic search strategy. CFS was evaluated by experiments on artificial and natural datasets. Three machine learning algorithms were used: C4.5 (a decision tree learner), IB1 (an instance based learner), and naive Bayes. Experiments
Improved heterogeneous distance functions
- Journal of Artificial Intelligence Research
, 1997
"... Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal input attributes appropriately. The Value Difference Metric (VDM) was designed to find reasonable distance values between nominal attribute values, but it largely ignores cont ..."
Abstract
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Cited by 290 (9 self)
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Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal input attributes appropriately. The Value Difference Metric (VDM) was designed to find reasonable distance values between nominal attribute values, but it largely ignores
CFT’s from Calabi-Yau Four-folds
- NUCL. PHYS. B584
, 1999
"... We consider F/M/Type IIA theory compactified to four, three, or two dimensions on a Calabi-Yau four-fold, and study the behavior near an isolated singularity in the presence of appropriate fluxes and branes. We analyze the vacuum and soliton structure of these models, and show that near an isolated ..."
Abstract
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Cited by 274 (15 self)
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We consider F/M/Type IIA theory compactified to four, three, or two dimensions on a Calabi-Yau four-fold, and study the behavior near an isolated singularity in the presence of appropriate fluxes and branes. We analyze the vacuum and soliton structure of these models, and show that near an isolated
A method for disambiguating word senses in a large corpus
- Computers and the Humanities
, 1992
"... Word sense disambiguation has been recognized as a major problem in natural language processing research for over forty years. Both quantitive and qualitative methods have been tried, but much of this work has been stymied by difficulties in acquiring appropriate lexical resources, such as semantic ..."
Abstract
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Cited by 273 (14 self)
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Word sense disambiguation has been recognized as a major problem in natural language processing research for over forty years. Both quantitive and qualitative methods have been tried, but much of this work has been stymied by difficulties in acquiring appropriate lexical resources, such as semantic
Wikify!: linking documents to encyclopedic knowledge
- In CIKM ’07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
, 2007
"... This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks. The paper also shows how the two methods can be combined into a system ..."
Abstract
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Cited by 265 (6 self)
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, as well as the assignment of links to appropriate related articles. For instance, Figure 1 shows an example of a Wikipedia page, including the definition for one of the meanings of the word “plant.”
Living with CLASSIC: When and How to Use a KL-ONE-Like Language
- Principles of Semantic Networks
, 1991
"... classic is a recently-developed knowledge representation system that follows the paradigm originally set out in the kl-one system: it concentrates on the definition of structured concepts, their organization into taxonomies, the creation and manipulation of individual instances of such concepts, ..."
Abstract
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Cited by 257 (18 self)
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classic is a recently-developed knowledge representation system that follows the paradigm originally set out in the kl-one system: it concentrates on the definition of structured concepts, their organization into taxonomies, the creation and manipulation of individual instances of such concepts
Results 1 - 10
of
3,181
