Term Statistics for Structured Text Retrieval
Inverse element frequency; Within-element term frequency
Classical ranking algorithms in information retrieval make use of term statistics, the most common (and basic) ones being within-document term frequency, tf, and document frequency, df. tf is the number of occurrences of a term in a document and is used to reflect how well a term captures the topic of a document, whereas df is the number of documents in which a term appears and is used to reflect how well a term discriminates between relevant and non-relevant documents. df is also commonly referred to as inverse document frequency, idf, since it is inversely related to the importance of a term. Both tf and idf are obtained at indexing time. Ranking algorithms for structured text retrieval, and more precisely XML retrieval, require similar terms statistics, but with respect to elements.
To calculate term statistics for elements, one could simply replace documents by elements and calculate so-called...
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