Search results
Results from the WOW.Com Content Network
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 ...
The formal study of relevance began in the 20th century with the study of what would later be called bibliometrics. In the 1930s and 1940s, S. C. Bradford used the term "relevant" to characterize articles relevant to a subject (cf., Bradford's law). In the 1950s, the first information retrieval systems emerged, and researchers noted the ...
Relevance (information retrieval) – Measure of a document's applicability to a given subject or search query; Relevance feedback – type of feedback; Rocchio classification – A classification model in machine learning based on centroids; Search engine indexing – Method for data management
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 .
Relevance is the connection between topics that makes one useful for dealing with the other. Relevance is studied in many different fields, including cognitive science, logic, and library and information science. Epistemology studies it in general, and different theories of knowledge have different implications for what is considered relevant.
A study found that a racially diverse workforce was positively associated with more customers, increased sales revenue, greater relative profits, and greater market share. The study also examined gender diversity and found it to be positively associated with increased sales revenue, more customers, and greater relative profits.23 Leveraging Talent
Pseudo-relevance feedback is efficient in average but can damage results for some queries, [7] especially difficult ones since the top retrieved documents are probably non-relevant. Pseudo-relevant documents are used to find expansion candidate terms that co-occur with many query terms. [ 8 ]
Maurizio Cattelan’s viral creation, titled “Comedian,” has proven a sound investment for one collector: One of the artwork’s three “editions” smashed estimates to sell for $6.24 ...