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Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types ...
Relevance level "Very low" – Information that is "three times removed" should not be included. For example, in the above "John Smith" article, "Murderer Larry Jones, also a member of the XYZ organization which John Smith belonged to, murdered 8 people."
On Wikipedia, relevance is simply whether a fact is in the right article, based on whether it pertains to the article's subject. Usually this is obvious. Usually this is obvious. When not obvious, relevance is decided by the editors of the article, based on what is considered likely to be useful to readers.
Once relevance levels have been assigned to the retrieved results, information retrieval performance measures can be used to assess the quality of a retrieval system's output. In contrast to this focus solely on topical relevance, the information science community has emphasized user studies that consider user relevance. [3]
2.1 Practical realities of "relevancy" in Wikipedia. 2.2 Guiding principles. 2.2.1 Content must be about the subject of the article.
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All of Wikipedia's content must be verifiable. The relevance of information is best demonstrated by the provision of reliable sources, and of suitable context. The bulk of Wikipedia's content consists of: Basic description – which explains what the subject is, what it does (or did), and what it is notable for.
The feedback form starts with a simple questions, then offers a comment box. The feedback form is a blue box at the bottom of Wikipedia articles, with a simple question: "Did you find what you were looking for?” and a comments box (see example above). For now, it is only available on a small test sample on the English Wikipedia.