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query-expansion

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This project implements a Document Retrieval System that integrates GPT-3.5-turbo for query expansion and answer generation. It fetches and ranks documents based on user queries, leveraging MongoDB for document storage, Redis for caching, and web scraping to keep documents updated. The system is designed to provide fast and accurate search results

  • Updated Sep 28, 2024
  • Python

Implementation of Probabilistic Retrieval Query expansion and Relevance Model based Language Modelling aimed at improving the precision of results using pseudo-relevance feedback in Information Retrieval.

  • Updated Nov 17, 2020
  • Python

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