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Automatic prediction of frustration

by Ashish Kapoor , Winslow Burleson , Rosalind W. Picard , 2007
"... Predicting when a person might be frustrated can provide an intelligent system with important information about when to initiate interaction. For example, an automated Learning Companion or Intelligent Tutoring System might use this information to intervene, providing support to the learner who is l ..."
Abstract - Cited by 99 (8 self) - Add to MetaCart
method was tested on data gathered from 24 participants using an automated Learning Companion. Their indication of frustration was automatically predicted from the collected data with 79% accuracy (chance 58%). The new assessment method is based on Gaussian process classification and Bayesian inference

Toward an instance theory of automatization

by Gordon D. Logan - Psychological Review , 1988
"... This article presents a theory in which automatization is construed as the acquisition of a domain-specific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur ..."
Abstract - Cited by 647 (38 self) - Add to MetaCart
This article presents a theory in which automatization is construed as the acquisition of a domain-specific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring

by T. R. Golub, D. K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J. P. Mesirov, H. Coller, M. L. Loh, J. R. Downing, M. A. Caligiuri, C. D. Bloomfield - Science , 1999
"... Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitori ..."
Abstract - Cited by 1779 (19 self) - Add to MetaCart
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression

Automatic Prediction Of Hit Songs

by Ruth Dhanaraj, Beth Logan - IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MUSIC INFORMATION RETRIEVAL (ISMIR , 2005
"... We explore the automatic analysis of music to identify likely hit songs. We extract both acoustic and lyric information from each song and separate hits from non-hits using standard classifiers, specifically Support Vector Machines and boosting classifiers. Our features are based on global sounds le ..."
Abstract - Cited by 15 (0 self) - Add to MetaCart
We explore the automatic analysis of music to identify likely hit songs. We extract both acoustic and lyric information from each song and separate hits from non-hits using standard classifiers, specifically Support Vector Machines and boosting classifiers. Our features are based on global sounds

Automatic prediction of parser accuracy

by Sujith Ravi, Kevin Knight, Radu Soricut - In EMNLP , 2008
"... Statistical parsers have become increasingly accurate, to the point where they are useful in many natural language applications. However, estimating parsing accuracy on a wide variety of domains and genres is still a challenge in the absence of gold-standard parse trees. In this paper, we propose a ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
technique that automatically takes into account certain characteristics of the domains of interest, and accurately predicts parser performance on data from these new domains. As a result, we have a cheap (no annotation involved) and effective recipe for measuring the performance of a statistical parser

AUTOMATIC PREDICTION AND MODEL SELECTION

by Maximiliano Marinucci , 2008
"... ..."
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Abstract not found

Query Expansion Using Local and Global Document Analysis

by Jinxi Xu, W. Bruce Croft - In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval , 1996
"... Automatic query expansion has long been suggested as a technique for dealing with the fundamental issue of word mismatch in information retrieval. A number of approaches to expansion have been studied and, more recently, attention has focused on techniques that analyze the corpus to discover word re ..."
Abstract - Cited by 610 (24 self) - Add to MetaCart
Automatic query expansion has long been suggested as a technique for dealing with the fundamental issue of word mismatch in information retrieval. A number of approaches to expansion have been studied and, more recently, attention has focused on techniques that analyze the corpus to discover word

Sparse Bayesian Learning and the Relevance Vector Machine

by Michael E. Tipping , 2001
"... This paper introduces a general Bayesian framework for obtaining sparse solutions to regression and classification tasks utilising models linear in the parameters. Although this framework is fully general, we illustrate our approach with a particular specialisation that we denote the `relevance vect ..."
Abstract - Cited by 966 (5 self) - Add to MetaCart
functions than a comparable SVM while offering a number of additional advantages. These include the benefits of probabilistic predictions, automatic estimation of `nuisance’ parameters, and the facility to utilise arbitrary basis functions (e.g. non-`Mercer’ kernels). We detail the Bayesian framework

Robust face recognition via sparse representation

by John Wright, Allen Y. Yang, Arvind Ganesh, S. Shankar Sastry, Yi Ma - IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2008
"... We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signa ..."
Abstract - Cited by 936 (40 self) - Add to MetaCart
We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse

Automatic Image Annotation and Retrieval using Cross-Media Relevance Models

by J. Jeon, V. Lavrenko, R. Manmatha , 2003
"... Libraries have traditionally used manual image annotation for indexing and then later retrieving their image collections. However, manual image annotation is an expensive and labor intensive procedure and hence there has been great interest in coming up with automatic ways to retrieve images based o ..."
Abstract - Cited by 431 (14 self) - Add to MetaCart
with annotations, we show that probabilistic models allow us to predict the probability of generating a word given the blobs in an image. This may be used to automatically annotate and retrieve images given a word as a query. We show that relevance models. allow us to derive these probabilities in a natural way
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