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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.
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