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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.
It is used interpretively if it represents some other utterance or thought, irrespective of the truth or state of affairs, as is the case with direct or indirect quotations, summaries, quoting folk wisdom, linguistic example sentences, tentative scientific hypotheses, et cetera. On a deeper level, every utterance is interpretive of a thought of ...
Various sentences using the syllables mā, má, mǎ, mà, and ma are often used to illustrate the importance of tones to foreign learners. One example: Chinese: 妈妈骑马马慢妈妈骂马; pinyin: māma qí mǎ, mǎ màn, māma mà mǎ; lit. 'Mother is riding a horse... the horse is slow... mother scolds the horse'. [37]
Relevance theory can therefore effortlessly account for the above example about Gérard: If B knows where Gérard lives, and "Somewhere in the South of France" is the most relevant answer compatible with B's preferences, it follows that B is unwilling to disclose his knowledge.
In order to evaluate how well an information retrieval system retrieved topically relevant results, the relevance of retrieved results must be quantified. In Cranfield-style evaluations, this typically involves assigning a relevance level to each retrieved result, a process known as relevance assessment. Relevance levels can be binary ...
"John Smith is a member of the XYZ organization" in the "John Smith" article is an example of this. Relevance level "Medium" – Information that is "once removed" is less directly relevant, should receive a higher level of scrutiny and achieve higher levels in other areas (such as neutrality, weight and strength [further explanation needed ...
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).
Relevance logic, also called relevant logic, is a kind of non-classical logic requiring the antecedent and consequent of implications to be relevantly related.