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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 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 ...
Rocchio Classification. In machine learning, a nearest centroid classifier or nearest prototype classifier is a classification model that assigns to observations the label of the class of training samples whose mean is closest to the observation.
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
Hofstede's cultural dimensions theory is a framework for cross-cultural psychology, developed by Geert Hofstede.It shows the effects of a society's culture on the values of its members, and how these values relate to behavior, using a structure derived from factor analysis.
Relevance theory only recognises three types of generic, universal speech acts: saying (that), telling (to), and asking (whether). Other speech acts are either culture specific or institutional rather than linguistic (for example, bidding at bridge, promising, or thanking); they have to be learned like all aspects of a culture, or
Cultural schema theory is a cognitive theory that explains how people organize and process information about events and objects in their cultural environment. [1] According to the theory, individuals rely on schemas, or mental frameworks, to understand and make sense of the world around them.
The probabilistic relevance model [1] [2] was devised by Stephen E. Robertson and Karen Spärck Jones as a framework for probabilistic models to come. It is a formalism of information retrieval useful to derive ranking functions used by search engines and web search engines in order to rank matching documents according to their relevance to a given search query.