Abstract: Graph Neural Networks (GNNs), which obtain node embeddings by attribute propagates along graph topology, exhibit significant power in graph-structured data mining ... text-rich graphs.

One method of obtaining such data is through the process of text and data mining (“TDM”) which involves systematic copying and analysis of data to gain insights. Consequently, issues crop up ...

Beatriz Rizkallah Alves (Neurology): A 71-year-old woman was transferred to this hospital for neurosurgical evaluation because of confusion ... The results of matrix-assisted laser desorption ...

and calculate the hazard ratio between the results captured using text mining and manual chart review. All analyses were performed using R software version 1.4.2. Fig 1. Confusion matrix for the ...

There are a lot of cases where automatic text classification would accelerate processing ... Using Unigrams/Bigrams Confusion Matrix for Support Vector Machine using Bag of Words Generated using clean ...

To make this information available for better dispatch control for power systems, a new text mining method ... and the bipartite graph is introduced to achieve a good clustering effect among ...

This study has the following contributions: first, text mining ... word” matrix. This paper has mainly made exploratory analysis based on the LDA model and has not set the expected results according ...

This prospective study was designed to propose a novel method of assessing proactive personality by combining text mining technology and Item Response Theory (IRT) to measure proactive personality ...

if no weight list (values: 0-1) is provided, a value of 1 is assumed; this value is used as weight for the counting then You don't have to write code for using the library, you can just use the ...