TF-IDF Ranking Function

AKA: TFIDF Rank.
Context:
- It can be used by an IR System (to solve an IR task).
Example(s):
- Given string [math]\displaystyle{ s }[/math] and Multiset [math]\displaystyle{ C }[/math] ...
- …
Counter-Example(s):
- a Constant Ranking Function.
- a Term Frequency Ranking Function.
See: Inverse Document Frequency, Information Retrieval, TF-IDF Vector.

References

(Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/TF-IDF
- … Variations of the tf–idf weighting scheme are often used by search engines as a central tool in scoring and ranking a document's relevance given a user query. One of the simplest ranking functions is computed by summing the tf-idf for each query term; many more sophisticated ranking functions are variants of this simple model.
http://en.wikipedia.org/wiki/Ranking_function
- Some very simple ranking functions include:
  - The constant ranking function assigning the same score to all documents.
  - The term frequency ranking function counting the number of times that each query term occurs in the document, then summing these.
  - The tf-idf ranking function computing the product of the term frequency and inverse document frequency for each query term, then multiplying these.

(Fagin et al., 2003b) ⇒ Ronald Fagin, Ravi Kumar, and D. Sivakumar. (2003). “Comparing Top k Lists.” In: Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete Algorithms.
(Aizawa, 2003) ⇒ Akiko Aizawa. (2003). “An Information-Theoretic Perspective of tf — idf Measures.” In: Information Processing and Management, 39(1). doi:10.1016/S0306-4573(02)00021-3

(Salton & McGill, 1983) ⇒ Gerard M. Salton, and Michael J. McGill. (1983). “Introduction to Modern Information Retrieval.” McGraw-Hill. ISBN:0070544840

(Salton et al, 1975) ⇒ Gerard M. Salton, A. Wong, and C. Yang. (1975). “A Vector Space Model for Automatic Indexing.” In: Communications of the ACM, 18(11).