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There are many reading strategies to use in improving reading comprehension and inferences, these include improving one's vocabulary, critical text analysis (intertextuality, actual events vs. narration of events, etc.), and practising deep reading. [11]
Text inferencing describes the tacit or active process of logical induction or deduction during reading. Inferences are used to bridge current text ideas with antecedent text ideas or ideas in the reader's store of prior world knowledge.
Additionally, the term 'inference' has also been applied to the process of generating predictions from trained neural networks. In this context, an 'inference engine' refers to the system or hardware performing these operations. This type of inference is widely used in applications ranging from image recognition to natural language processing.
Rules of inference are syntactical transform rules which one can use to infer a conclusion from a premise to create an argument. A set of rules can be used to infer ...
Deductively valid arguments follow a rule of inference. [38] A rule of inference is a scheme of drawing conclusions that depends only on the logical form of the premises and the conclusion but not on their specific content. [39] [40] The most-discussed rule of inference is the modus ponens. It has the following form: p; if p then q; therefore q.
Backward chaining (or backward reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, proof assistants, and other artificial intelligence applications. [1]
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