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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 ...
Its purpose is to help editors improve the article based on reader feedback. To see the feedback page for this test sample, click on “Talk” at the top of the article page; then click on “View reader feedback” at the top of the talk page. For example, take a look at the feedback page for the Golden-crowned Sparrow. (Tech note: feedback ...
Following is an approach to determine and name degrees of relevance and how to utilize the results: Relevance level "High" – The highest relevance is objective information directly about the topic of the article. "John Smith is a member of the XYZ organization" in the "John Smith" article is an example of this.
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]
You can view feedback in a number of places: This central feedback page for all of Wikipedia; This sample article feedback page; On other articles with feedback, (Look for a link on these article talkpages to see feedback. Note that only about 10 percent of articles have feedback so far.)
Its purpose is to help editors improve the article based on reader feedback. To see the feedback page for this test sample, click on “Talk” at the top of the article page; then click on “View reader feedback” at the top of the talk page. For example, take a look at the feedback page for the Golden-crowned Sparrow.
Article feedback was found at the bottom of many Wikipedia articles; it is a simple form that readers can use to submit suggestions for improvement. (See screenshot below.) These suggestions are then reviewed by Wikipedia contributors, who can identify and take action on useful feedback -- while ignoring or removing bad submissions.
Chart 1: All non-list articles Chart 2: Top-, high- and mid-importance articles Chart 3: GA, A and FA. Statistics for the English Wikipedia derived from Wikipedia:Version 1.0 Editorial Team/Statistics as of 2017-05-17 follow. Where an article has been rated for quality and/or importance by more than one project, the highest quality and ...