tensorflow / tensorflow/recommenders

How to know the Rank model improves the output of the Retrieval model in the case of MovieLens dataset?

Open
#690 15 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
2k
Forks
300
PR merge metrics
No merged PRs in 30d

Description

We all know that the rank will enhance the output of the retrieval model. But how can we see that in the case of MovieLens dataset?

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue names the MovieLens dataset and the Retrieval and Rank models but provides no file, test, or entry point. Start by locating their evaluation code, then establish a reproducible comparison showing whether ranking improves retrieval output on MovieLens; done means the evaluation method and result are documented.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, tensorflow
Domain
machine-learning
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.