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relevance-feedback

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This project implements advanced image retrieval techniques for Caltech101 dataset, using algorithms like MDS, SVD, DBScan, and Locality Sensitive Hashing (LSH). It focuses on optimizing retrieval accuracy and efficiency through dimensionality reduction, clustering, classification, and relevance feedback, enhancing multimedia search capabilities.

  • Updated Nov 30, 2023
  • Jupyter Notebook

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

Dice.com's relevancy feedback solr plugin created by Simon Hughes (Dice). Contains request handlers for doing MLT style recommendations, conceptual search, semantic search and personalized search

  • Updated May 12, 2021
  • Java

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