An R-tool for comprehensive science mapping analysis. A package for quantitative research in scientometrics and bibliometrics.
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Updated
Jul 2, 2024 - R
An R-tool for comprehensive science mapping analysis. A package for quantitative research in scientometrics and bibliometrics.
Inference of microbial interaction networks from large-scale heterogeneous abundance data
This repository contains the data used for and generated during our research for the article "Neo-Assyrian Imperial Religion Counts: A Quantitative Approach to the Affiliations of Kings and Queens with their Gods and Goddesses." The creation of this data has been funded by the Academy of Finland (decision numbers 298647, 312051, and 330727).
Scripts to convert correlation and p-value matrices to edge list and network
It is important for a granting agency to know how the distribution of the applications qua disciplines is. ˆ How many applications belong to Exact Science disciplines, how many fall within one discipline? ˆ How many applications with disciplines outside exact sciences domain have been submitted?
Compared the agenda setting strategies on the "Ractopamine Pork" Vote, one of the four questions in the 2021 Taiwanese Referendum, between pan-blue and pan-green media by using text mining approaches such as bag-of-words, w2v, topic model. Raw data were collected from four Taiwanese media (Chinatimes/TVBS/LTN/FTV) with Python Package BeautifulSoup.
NLP Project 2 - Using ount Vector, TF-IDF Vector, Co-occurrence Matrix for Frequency based embeddings and made Word2Vec model using Continuous Bag of Words (CBOW) and Skip-Gram (SG) for Prediction based Embeddings
R package for analyzing microbial co-occurences
Text Processing Using Hadoop
Calculates the probability of co-occurrence from gray-scale images.
Code and data for extracting co-occurrence networks from Shakespeare's plays
Texture Segmentation using: Gray-Level Co-occurence Matrix, Leung-Malik (LM) Filter Bank and Schmid (S) Filter Bank and Local Binary Pattern.
Co-occurrence Based Texture Synthesis
Work in Fintech-Text-Mining-and-Machine-Learning class
A fast implementation of GloVe, with optional retrofitting
Data aggregation | Big Data Analysis | Visualization
Data Analytics pipeline using Apache Spark | Build multi-class classification models | Test the model using test data and compute accuracy of each method
Tool for extracting topics, keywords and their collocates from a Dutch corpus. Includes and extends the functionality of the Keyword Generator.
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