Results 261 to 270 of about 118,657 (309)
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LDA for on-the-fly auto tagging
Proceedings of the fourth ACM conference on Recommender systems, 2010In this paper, we propose a method for automatic tagging sparse and short textual resources. In the presence of a new resource, our method creates an ad hoc corpus of related resources, then applies Latent Dirichlet Allocation (LDA) to elicit latent topics for the resource and the associated corpus.
Ernesto Diaz-Aviles +3 more
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Deep LDA : A new way to topic model
Journal of Information and Optimization Sciences, 2019Probabilistic topic models like Latent Semantic Indexing (LSI), Latent Dirichlet Allocation (LDA) and Biterm Topic Model (BTM) have been successfully implemented and used in many areas like movie reviews, recommender systems and text summarization etc ...
M. Bhat +3 more
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WT-LDA: User Tagging Augmented LDA for Web Service Clustering
2013Clustering Web services that groups together services with similar functionalities helps improve both the accuracy and efficiency of the Web service search engines. An important limitation of existing Web service clustering approaches is that they solely focus on utilizing WSDL Web Service Description Language documents.
Liang Chen 0001 +4 more
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, 2019
This study addressed the detection and classification of biodiesel from different sources using electronic nose through application of statistical training-based methods and mathematical optimization techniques.
Korosh Mahmodi +2 more
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This study addressed the detection and classification of biodiesel from different sources using electronic nose through application of statistical training-based methods and mathematical optimization techniques.
Korosh Mahmodi +2 more
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Supervised LDA for Image Annotation
2011 IEEE International Conference on Systems, Man, and Cybernetics, 2011Region-based Image Annotation has received increasing attention in recent years. Topic models such as probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA) have shown great success in object recognition and localization. In this paper, we introduce a supervised topic model for region-based image annotation.
Qiaojin Guo +3 more
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Pattern Recognition Letters, 2005
In this paper, we prove that the principal component analysis (PCA) and the linear discriminant analysis (LDA) can be directly implemented in the discrete cosine transform (DCT) domain and the results are exactly the same as the one obtained from the spatial domain. In some applications, compressed images are desirable to reduce the storage requirement.
Weilong Chen, Meng Joo Er, Shiqian Wu
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In this paper, we prove that the principal component analysis (PCA) and the linear discriminant analysis (LDA) can be directly implemented in the discrete cosine transform (DCT) domain and the results are exactly the same as the one obtained from the spatial domain. In some applications, compressed images are desirable to reduce the storage requirement.
Weilong Chen, Meng Joo Er, Shiqian Wu
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18th International Conference on Pattern Recognition (ICPR'06), 2006
We propose an alternative to probability density classifiers based on normal distributions LDA and QDA. Instead of estimating covariance matrices using the standard maximum likelihood estimator we estimate class domains by the minimum volume enclosing ellipsoid (i-MVEE). The i-MVEE is a robust statistic rejecting a specified fraction i of the data. The
Piotr Juszczak +3 more
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We propose an alternative to probability density classifiers based on normal distributions LDA and QDA. Instead of estimating covariance matrices using the standard maximum likelihood estimator we estimate class domains by the minimum volume enclosing ellipsoid (i-MVEE). The i-MVEE is a robust statistic rejecting a specified fraction i of the data. The
Piotr Juszczak +3 more
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Journal of Software: Evolution and Process, 2016
AbstractLatent Dirichlet allocation (LDA) has seen increasing use in the understanding of source code and its related artifacts in part because of its impressive modeling power. However, this expressive power comes at a cost: The technique includes several tuning parameters whose impact on the resulting LDA model must be carefully considered.
David W. Binkley +3 more
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AbstractLatent Dirichlet allocation (LDA) has seen increasing use in the understanding of source code and its related artifacts in part because of its impressive modeling power. However, this expressive power comes at a cost: The technique includes several tuning parameters whose impact on the resulting LDA model must be carefully considered.
David W. Binkley +3 more
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Exchange interactions in (ZnMn)Se: LDA and LDA+U calculations
Physical Review B, 2003One of the remarkable properties of the II-VI diluted magnetic semiconductor (ZnMn)Se is the giant spin splitting of the valence-band states under application of the magnetic field (giant Zeeman splitting). This splitting reveals strong exchange interaction between Mn moments and semiconductor states. On the other hand, no magnetic phase transition has
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