Using TF-IDF to Determine Word Relevance in Document Queries :

In this paper, we examine the results of applying

Term Frequency Inverse Document Frequency

(TF-IDF) to determine what words in a corpus of

documents might be more favorable to use in a

query. As the term implies, TF-IDF calculates

values for each word in a document through an

inverse proportion of the frequency of the word

in a particular document to the percentage of

documents the word appears in. Words with

high TF-IDF numbers imply a strong

relationship with the document they appear in,

suggesting that if that word were to appear in a

query, the document could be of interest to the

user. We provide evidence that this simple

algorithm efficiently categorizes relevant words

that can enhance query retri