Results 131 to 140 of about 63,472 (294)

Extending Information Retrieval Methods to Personalized Genomic-Based Studies of Disease

open access: yesCancer Informatics, 2014
Genomic-based studies of disease now involve diverse types of data collected on large groups of patients. A major challenge facing statistical scientists is how best to combine the data, extract important features, and comprehensively characterize the ...
Shuyun Ye   +2 more
doaj   +1 more source

Automating the analysis of public saliency and attitudes toward biodiversity from digital media

open access: yesConservation Biology, EarlyView.
Abstract Measuring public attitudes toward wildlife provides crucial insights into human relationships with nature and helps monitor progress toward Global Biodiversity Framework targets. Yet, conducting such assessments at a global scale presents challenges.
Noah Giebink   +8 more
wiley   +1 more source

Latent Dirichlet Allocation Uncovers Spectral Characteristics of Drought Stressed Plants

open access: yes, 2012
Understanding the adaptation process of plants to drought stress is essential in improving management practices, breeding strategies as well as engineering viable crops for a sustainable agriculture in the coming decades.
Ballvora, Agim   +8 more
core  

Selecting Priors for Latent Dirichlet Allocation

open access: yes2018 IEEE 12th International Conference on Semantic Computing (ICSC), 2018
Latent Dirichlet Allocation (LDA) has gained much attention from researchers and is increasingly being applied to uncover underlying semantic structures from a variety of corpora. However, nearly all researchers use symmetrical Dirichlet priors, often unaware of the underlying practical implications that they bear. This research is the first to explore
Syed, Shaheen, Spruit, Marco
openaire   +3 more sources

Leveraging online reviews to decode quality‐induced customer dissatisfaction: From perception to product discouragement

open access: yesDecision Sciences, EarlyView.
Abstract E‐commerce practitioners and researchers recognize that quality concerns are the primary drivers of customer dissatisfaction with products or services. While dissatisfaction can arise from various factors, little is known about quality and its components, specifically from the perspective of dissatisfied customers. Grounded in the foundational
Rahul Kumar   +4 more
wiley   +1 more source

Race‐related research in economics

open access: yesEconomica, EarlyView.
Abstract Issues of racial justice and economic inequalities between racial and ethnic groups have risen to the top of public debate. Economists' ability to contribute to these debates is based on the body of race‐related research. We study the volume and content of race‐related research in economics.
Arun Advani   +4 more
wiley   +1 more source

Scalable Inference for Latent Dirichlet Allocation

open access: yes, 2009
We investigate the problem of learning a topic model - the well-known Latent Dirichlet Allocation - in a distributed manner, using a cluster of C processors and dividing the corpus to be learned equally among them. We propose a simple approximated method that can be tuned, trading speed for accuracy according to the task at hand.
Petterson, James, Caetano, Tiberio
openaire   +2 more sources

The power of a stewardship mind: Reorienting organizations around the duty to care to better address grand challenges

open access: yesInternational Journal of Management Reviews, EarlyView.
Abstract The present article presents an integrative review related to stewardship in all the business and management disciplines, from its initial development in 1980 to the present. Specifically, we applied a latent Dirichlet allocation‐based topic modelling analysis to almost 1200 articles, seeking to creatively synthesize the concept of stewardship
Debora Casoli   +3 more
wiley   +1 more source

Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels

open access: yesInternational Statistical Review, EarlyView.
Summary Bayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted.
Wei Jing   +2 more
wiley   +1 more source

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