Detecting the Evolving Community Structure in Dynamic Social Networks (WWWJ 2020)
-
Updated
Jun 23, 2020 - MATLAB
Detecting the Evolving Community Structure in Dynamic Social Networks (WWWJ 2020)
Evolutionary Community Detection in Dynamic Social Networks (IJCNN 2019)
Project work done as part of Udacity's Data Analyst Nanodegree course.
Email Datasets can be found here
C++ File Search Engine for Enron Email Sample Dataset
Developed a Naive Bayes classifier for classifying the E-mail is Spam or Ham message
A priority based email queue solution to address this problem. Also, further extended this feature with an automatic response recommendation that would help in cleaning mails faster.
This repository contains code for normalizing the Enron dataset.
Enron emails: indexer, apiREST, and visulizer.
Machine learning algorithms applied to explore Enron email dataset and figure out patterns about people involved in the scandal.
An application which converts Enron dataset into a single CSV file
This is a Spam/Ham detector using Naive Bayes classifier implemented from scratch in Python3. It is currently trained on Enron dataset.
Phishing Detection classifier to filter fraudolent and phishing e-mail.
Distributed Real Time Spam Classification using Apache Spark
The Indexer crawls over the enron email dataset folders and indexed each file in the ZincSearch database. It also have a User Interface built with vue which allows you to search over the indexed files based on a keyword.
C-blondel: an efficient louvain-based dynamic community detection algorithm
Maximizing Enron's Goldmine with Topic Modeling & Summarization
Add a description, image, and links to the enron-email-dataset topic page so that developers can more easily learn about it.
To associate your repository with the enron-email-dataset topic, visit your repo's landing page and select "manage topics."