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.
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Updated
Nov 17, 2020 - 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.
A search engine that takes keyword queries as input and retrieves a ranked list of relevant results as output. It scraps a few thousand pages from one of the seed Wiki pages and uses Elasticsearch for a full-text search engine.
Information retrieval system that gives ranked results when a query is given
Using Apache Lucene to index documents in AP89 corpus, perform retrieval on TREC topics and evaluate the performance of retrieval algorithms using different evaluation metrics
Ranks passages against queries using various models and techniques.
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