# Time-weighted vector store retriever

This retriever uses a combination of semantic similarity and a time decay.

The algorithm for scoring them is:

```
semantic_similarity + (1.0 - decay_rate) ^ hours_passed
```

Notably, `hours_passed` refers to the hours passed since the object in the retriever **was last accessed**, not since it was created. This means that frequently accessed objects remain "fresh."

import Example from "@snippets/modules/data_connection/retrievers/how_to/time_weighted_vectorstore.mdx"

<Example/>
