big data project to generate random text and analyse co-occurence matrix

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

Movie Recommender System based on co-occurrence matrix/similarity matrix.

Text Processing using Pyspark

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

Co Occurrence Filter Matlab implementation.

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

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

Data aggregation | Big Data Analysis | Visualization

A fast implementation of GloVe, with optional retrofitting

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

Co-occurrence Based Texture Synthesis

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

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

Text Processing Using Hadoop

R package for analyzing microbial co-occurences

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

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.