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This blog documents the process of implementing a search engine that takes a query term as input and ranks relevant documents in the corpus. The corpus, in this case is a collection of random documents, that is, wiki’s of a tv show’s prominent characters, a movie franchise, a country, a social media company and a type of fish. Code at : amrtanair/search-engine Breaking down the problem and the approach The first step was to create the inverted index(a dictionary that stores the mapping of a ter...