<information science> A search based on frequencies of the search terms in the documents being searched. Weighted search is often used by search engines. It produces a numerical score for each possible document. A document's score depends on the frequency of each search term in that document compared with the overall frequency of that term in the entire corpus of documents. A common approach is called tf.idf which stands for term frequency * inverse document frequency. Term frequency means "the more often a term occurs in a document, the more important it is in describing that document." http://ciir.cs.umass.edu/cmpsci646/ir4/tsld034.htm Inverse document frequency means the more documents a term appears in, the less important the term is. A simple weighted search is just a list of search terms, for example: car automobile Weighted search is often contrasted with boolean search. It is possible to have a search that syntactically is a boolean search but which also does a weighted search. See also query expansion. For a detailed technical discussion see Chapter 5, "Search Strategies", in the reference below. [{"Information Retrieval", C. J. van Rijsbergen, (http://dcs.gla.ac.uk/Keith/Chapter.5/Ch.5.html)}]. (1999-08-28)

In finance, the weighted-average life (WAL) of an amortizing loan or amortizing bond, also called average life,PIMCO glossaryBloomberg Glossary is the weighted average of the times of the principal repayments: it's the average time until a dollar of principal is repaid.

In applied mathematics, methods of mean weighted residuals (MWR) are methods for solving differential equations. The solutions of these differential equations are assumed to be well approximated by a finite sum of test functions \phi_i.