Results 221 to 230 of about 306,626 (287)

Topic recognition and refined evolution path analysis of literature in the field of cybersecurity. [PDF]

PLoS One
Zhu Y, Li Z, Li T, Jiang L.
europepmc   +1 more source

Detection of Adulteration of Extra Virgin Olive Oil via Laser-Induced Breakdown Spectroscopy and Ultraviolet-Visible-Near-Infrared Absorption Spectroscopy: A Comparative Study. [PDF]

Foods
Nanou E, Bekogianni M, Stamatoukos T, Couris S.   +3 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Concept-LDA: Incorporating Babelfy into LDA for aspect extraction

Journal of Information Science, 2019
Latent Dirichlet allocation (LDA) is one of the probabilistic topic models; it discovers the latent topic structure in a document collection. The basic assumption under LDA is that documents are viewed as a probabilistic mixture of latent topics; a topic has a probability distribution over words and each document is modelled on the basis of a bag-of ...
Ekin Ekinci, Sevinç İlhan Omurca
openaire   +4 more sources

Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis

2016 International Joint Conference on Neural Networks (IJCNN), 2016
The advent of the Social Web has provided netizens with new tools for creating and sharing, in a time- and cost-efficient way, their contents, ideas, and opinions with virtually the millions of people connected to the World Wide Web. This huge amount of information, however, is mainly unstructured as specifically produced for human consumption and ...
Federica Bisio, Erik Cambria, Soujanya Poria, Iti Chaturvedi   +3 more
openaire   +3 more sources

CapsNet-LDA: predicting lncRNA-disease associations using attention mechanism and capsule network based on multi-view data

Briefings Bioinform., 2022
Cumulative studies have shown that many long non-coding RNAs (lncRNAs) are crucial in a number of diseases. Predicting potential lncRNA-disease associations (LDAs) can facilitate disease prevention, diagnosis and treatment.
Zequn Zhang, Junlin Xu, Yanan Wu, Nian-Nian Liu, Yinglong Wang, Ying Liang   +5 more
semanticscholar   +1 more source

Self-Weighted Unsupervised LDA

IEEE Transactions on Neural Networks and Learning Systems, 2023
As a hot topic in unsupervised learning, clustering methods have been greatly developed. However, the model becomes more and more complex, and the number of parameters becomes more and more with the continuous development of clustering methods. And parameter-tuning in most methods is a laborious work due to its complexity and unpredictability.
Xuelong Li, Yunxing Zhang, Rui Zhang
openaire   +2 more sources

Equivalence between LDA/QR and Direct LDA

International Journal of Cognitive Informatics and Natural Intelligence, 2011
Singularity problems of scatter matrices in Linear Discriminant Analysis (LDA) are challenging and have obtained attention during the last decade. Linear Discriminant Analysis via QR decomposition (LDA/QR) and Direct Linear Discriminant analysis (DLDA) are two popular algorithms to solve the singularity problem.
Shuang Liang, Eddie C. L. Chan, Rong-Hua Li, George Baciu   +3 more
openaire   +2 more sources