Incorporating Time-Dependent Interactions
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Description
Hi,
In Rendle's original paper on FM (https://www.csie.ntu.edu.tw/~b97053/paper/Rendle2010FM.pdf), he used a feature that captures the time of the user-item interaction. This should improve the model.
In your model, from what I see, we can input user features, item features and the interactions themselves.
How can I add the time of the interaction into the mix?
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the LightFM model input and feature APIs to understand how user features, item features, and interactions are currently represented. Then compare those capabilities with the time-dependent interaction described in the linked Rendle paper. Done would require a clearly defined, supported way to incorporate interaction time, or documentation explaining the limitation.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100