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Update links on QA Use Case docs (#8784)
- Description: 2 links were not working on Question Answering Use Cases documentation page. Hence, changed them to nearest useful links, - Issue: NA, - Dependencies: NA, - Tag maintainer: @baskaryan, - Twitter handle: NA <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! Please make sure you're PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. Maintainer responsibilities: - General / Misc / if you don't know who to tag: @baskaryan - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev - Models / Prompts: @hwchase17, @baskaryan - Memory: @hwchase17 - Agents / Tools / Toolkits: @hinthornw - Tracing / Callbacks: @agola11 - Async: @agola11 If no one reviews your PR within a few days, feel free to @-mention the same people again. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md -->
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@ -138,9 +138,9 @@ len(docs_svm)
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Some common ways to improve on vector similarity search include:
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- `MultiQueryRetriever` [generates variants of the input question](/docs/modules/data_connection/retrievers/how_to/MultiQueryRetriever) to improve retrieval.
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- `MultiQueryRetriever` [generates variants of the input question](/docs/modules/data_connection/retrievers/MultiQueryRetriever) to improve retrieval.
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- `Max marginal relevance` selects for [relevance and diversity](https://www.cs.cmu.edu/~jgc/publication/The_Use_MMR_Diversity_Based_LTMIR_1998.pdf) among the retrieved documents.
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- Documents can be filtered during retrieval using [`metadata` filters](/docs/use_cases/question_answering/document-context-aware-QA).
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- Documents can be filtered during retrieval using [`metadata` filters](/docs/use_cases/question_answering/how_to/document-context-aware-QA).
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```python
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