Add algo for calculation of sorrelation between two problems
Fetch user activity details from Erdos into db
Fetch user activity details from Codeforces into db
Calculate problem diffiulty for a user based on his attempt count and submission status
Add created_at field in activity table
Function to fetch user lists
Modify function to fetch user activity to consider only the submissions made after last saved activity
Add function to create a difficulty matrix from activity table
Function to fetch user activity for all users
- Function to calculate Pearson correlation score for two users
- Function to find similar users based on correlation score
Function to recommend new problems based on user correlation scores
Function to recommend correlated problems
Add a check for problem in database before printing its details
Change correlation algorithm to account for number of common problems/users and total problems/users
Small changes:
- Add main to problem.py
- Fix Codeforces user list URL
- Fix problem difficulty calculation
- check availability of handle in difficulty matrix before calculating correlation
Normalize difficulty matrix before calculating user similarity
Evaluate estimated error in recommendation based on user's attempted problems
using tf-idf for assigning weights to tags in a problem and creating db connections for the class instance instead of individual functions
using tf-idf for assigning weights to tags in a problem and creating db connections for the class instance instead of individual functions and modified the normalisation factor as well
added results with the current implementation