An R-tool for comprehensive science mapping analysis. A package for quantitative research in scientometrics and bibliometrics.

• UpdatedMar 19, 2025
• R

Inference of microbial interaction networks from large-scale heterogeneous abundance data

• UpdatedJun 6, 2024
• Julia

Deep Co-occurrence Feature Learning for Visual Object Recognition (CVPR 2017)

• UpdatedMay 15, 2017
• MATLAB

Co-occurrence Based Texture Synthesis

• UpdatedMay 19, 2020
• Python

Code and data for extracting co-occurrence networks from Shakespeare's plays

• UpdatedJan 16, 2025
• Python

A fast implementation of GloVe, with optional retrofitting

• UpdatedApr 16, 2019
• Python

Tool for extracting topics, keywords and their collocates from a Dutch corpus. Includes and extends the functionality of the Keyword Generator.

• UpdatedSep 3, 2018
• Python

Text Processing Using Hadoop

• UpdatedMar 3, 2022
• Jupyter Notebook

Unlabeled directed graph mining project from Co-occurrence graph of Document using gSpan algorithm based on Apache Spark

• UpdatedJan 10, 2018
• Scala

Texture Segmentation using: Gray-Level Co-occurence Matrix, Leung-Malik (LM) Filter Bank and Schmid (S) Filter Bank and Local Binary Pattern.

• UpdatedJan 22, 2021
• Jupyter Notebook

Co Occurrence Filter Matlab implementation.

• UpdatedFeb 7, 2018
• MATLAB

Work in Fintech-Text-Mining-and-Machine-Learning class

• UpdatedAug 7, 2019
• Jupyter Notebook

• UpdatedMar 11, 2021
• Jupyter Notebook

R package for analyzing microbial co-occurences

• UpdatedMar 10, 2022
• R

Data Analytics pipeline using Apache Spark | Build multi-class classification models | Test the model using test data and compute accuracy of each method

• UpdatedOct 14, 2018
• Python

Calculates the probability of co-occurrence from gray-scale images.

• UpdatedNov 17, 2021
• C++

Text Processing using Pyspark

• UpdatedSep 13, 2017
• Jupyter Notebook

• UpdatedJan 17, 2021
• Python

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

• UpdatedApr 15, 2022
• Python

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?

• UpdatedJan 7, 2023
• Jupyter Notebook