نتایج جستجو برای: latent class clustering
تعداد نتایج: 545339 فیلتر نتایج به سال:
This paper presents an algorithm for finding the maximum a posteriori (MAP) clustering in a class of univariate product partition models. While the number of possible clusterings of n observations grows according to the Bell exponential number, the dynamic programming algorithm presented here exploits properties of the model to provide an O(n2) search. Hence, the algorithm can be used to find t...
Clustering approaches have been widely used in process control community for unsupervised classification beneficial for further analysis, modeling and optimization. Process data generally involve far more dimensions than needed; this phenomenon is called as ”data rich but information poor” and becomes obstacles for reasonable classification. Therefore, it is desirable to use latent variable mod...
In latent semantic analysis (LSA), we aim at modelling a large corpus of high-dimensional discrete data from probabilistic perspective. The Assumption: one data point can be modelled by latent factors, which account for the co-occurrence of items within the data. We are also interested in the clustering structure of the data, which may benefit from the latent factors of the items. For example: ...
This paper focuses on service clustering and uses service descriptions to construct probabilistic models for service clustering. We discuss how service descriptions can be enriched with machine-interpretable semantics and then we investigate how these service descriptions can be grouped in clusters in order to make discovery, ranking, and recommendation faster and more effective. We propose usi...
We review the class of continuous latent space (statistical) models for network data, paying particular attention to the role of the geometry of the latent space. In these models, the presence/absence of network dyadic ties are assumed to be conditionally independent given the dyads? unobserved positions in a latent space. In this way, these models provide a probabilistic framework for embeddin...
This paper focuses on service clustering and uses service descriptions to construct probabilistic models for service clustering. We discuss how service descriptions can be enriched with machine-interpretable semantics and then we investigate how these service descriptions can be grouped in clusters in order to make discovery, ranking, and recommendation faster and more effective. We propose usi...
BACKGROUND Previous studies have reported that the current DSM-IV eating disorder (ED) criteria do not adequately describe ED symptomatology. The objective of the current study was to examine the clustering of ED symptoms in a general population sample using latent class analysis (LCA). METHOD ED symptoms from 3723 female young adult twins (mean age 22) were analyzed using LCA, and resulting ...
We describe an adaptation of the simulated annealing algorithm to nonparametric clustering and related probabilistic models. This new algorithm learns nonparametric latent structure over a growing and constantly churning subsample of training data, where the portion of data subsampled can be interpreted as the inverse temperature β(t) in an annealing schedule. Gibbs sampling at high temperature...
Probabilistic Latent Semantic Analysis (PLSA) has become a popular topic model for image clustering. However, the traditional PLSA method considers each image (document) independently, which would often be conflict with the real occasion. In this paper, we presents an improved PLSA model, named Correlated Probabilistic Latent Semantic Analysis (C-PLSA). Different from PLSA, the topics of the gi...
This paper reports on the experiments and results of a clustering approach used in the INEX 2008 Document Mining Challenge. The clustering approach utilizes both the structure and the content information of the XML documents in the Wikipedia collection. The content of the XML documents is measured using the latent semantic kernel (LSK). A well-known problem with the construction of latent seman...
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