Search

In this assessment, you'll implement a basic search engine by defining your own Python classes. A search engine is an algorithm that takes a query and retrieves the most relevant documents for that query. In order to identify the most relevant documents, our search engine will use term frequency$$inverse document frequency $($tf$$idf$),$ an information statistic for determining the relevance of a term to each document from a corpus consisting of many documents.

The tf$$idf statistic consists of two components: term frequency and inverse document frequency. Term frequency computes the number of times that a term appears in a document $($such as a single Wikipedia page$).$ If we were to use only the term frequency in determining the relevance of a term to each document, then our search result might not be helpful since most documents contain many common words such as "the" or $"$a$".$ In order to downweight these common terms, the document frequency computes the number of times that a term appears across the corpus of all documents. The tf$$idf statistic takes a term and a document and returns the term frequency divided by the document frequency.