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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 ...
However, some statements in the article are biased. Please remember that all articles must be written from a neutral point of view. Here are some tips to help you write unbiased articles." If you regularly respond to requests for feedback here, please consider adding the following userbox to your userpage: {{Wikipedia:Requests for feedback ...
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.
The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model .
The information retrieval community has emphasized the use of test collections and benchmark tasks to measure topical relevance, starting with the Cranfield Experiments of the early 1960s and culminating in the TREC evaluations that continue to this day as the main evaluation framework for information retrieval research.
Relevance level "Lower" – Information that is "twice removed" should usually not be included unless the other considerations described above are unusually strong. For example, in the above "John Smith" article, "Murderer Larry Jones was also a member of the XYZ organization."
2.1 Practical realities of "relevancy" in Wikipedia. 2.2 Guiding principles. 2.2.1 Content must be about the subject of the article.
To enable the Article Feedback Tool on articles you watch, simply add this special category ('Category:Article_Feedback_5') on your articles -- and the feedback form will automatically appear at the bottom of these pages. Editors who add this tool are encouraged to moderate feedback periodically for those articles (using the 'reader feedback ...