Using TF-IDF to Determine Word Relevance in Document Queries
نویسنده
چکیده
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 retrieval.
منابع مشابه
Comparative Analysis of IDF Methods to Determine Word Relevance in Web Document
Inverse document frequency (IDF) is one of the most useful and widely used concepts in information retrieval. When it is used in combination with the term frequency (TF), the result is a very effective term weighting scheme (TF-IDF) that has been applied in information retrieval to determine the weight of the terms. Terms with high TF-IDF values imply a strong relationship with the document the...
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