A probabilistic generative model for GO enrichment analysis

A probabilistic generative model for GO enrichment analysis

The Gene Ontology (GO) is extensively used to analyze all types of high-throughput experiments. However, researchers still face several challenges when using GO and other functional annotation databases. One problem is the large number of multiple hypotheses that are being tested for each study. In addition, categories often overlap with both direct parents/descendents and other distant categor...

Probabilistic acoustic tube: a probabilistic generative model of speech for speech analysis/synthesis

PROMODES: A Probabilistic Generative Model for Word Decomposition

For the Morpho Challenge 2009 we present an algorithm for unsupervised morphological analysis called Promodes1 which is based on a probabilistic generative model. The model considers segment boundaries as hidden variables and includes probabilities for letter transitions within segments. Promodes purely concentrates on segmenting words whereas its labeling method is simplistic. Morpheme labels ...

A Probabilistic Generative Model for Latent Business Networks Mining

The structural embeddedness theory posits that a company’s embeddedness in a business network impacts its competitive performance. This highlights the theoretical and practical values toward business network mining and analysis. Given the fact that latent business relationships exist among companies, and these relationships continuously evolve over time, a manual approach for the discovery and ...

Exploring Social Influence for Recommendation - A Probabilistic Generative Model Approach

In this paper, we propose a probabilistic generative model, called unified model, which naturally unifies the ideas of social influence, collaborative filtering and content-based methods for item recommendation. To address the issue of hidden social influence, we devise new algorithms to learn the model parameters of our proposal based on expectation maximization (EM). In addition to a single-m...