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An alternative direction is to aggregate word embeddings, such as those returned by Word2vec, into sentence embeddings. The most straightforward approach is to simply compute the average of word vectors, known as continuous bag-of-words (CBOW). [9] However, more elaborate solutions based on word vector quantization have also been proposed.
[5] The type of inference drawn here is also called a "causal inference" because the inference made suggests that events in one sentence cause those in the next. Backward inferences can be either logical, in that the reader assumes one occurrence based on the statement of another, or pragmatic, in that the inference helps the reader comprehend ...
know the meaning of words, understand the meaning of a word from a discourse context, follow the organization of a passage and to identify antecedents and references in it, draw inferences from a passage about its contents, identify the main thought of a passage, ask questions about the text, answer questions asked in a passage, visualize the text,
In the TE framework, the entailing and entailed texts are termed text (t) and hypothesis (h), respectively.Textual entailment is not the same as pure logical entailment – it has a more relaxed definition: "t entails h" (t ⇒ h) if, typically, a human reading t would infer that h is most likely true. [1]
The validity of an inference depends on the form of the inference. That is, the word "valid" does not refer to the truth of the premises or the conclusion, but rather to the form of the inference. An inference can be valid even if the parts are false, and can be invalid even if some parts are true.
Grammar induction (or grammatical inference) [1] is the process in machine learning of learning a formal grammar (usually as a collection of re-write rules or productions or alternatively as a finite-state machine or automaton of some kind) from a set of observations, thus constructing a model which accounts for the characteristics of the observed objects.
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The task is to infer which of two alternatives has the higher criterion value. An example is which of two NBA teams will win the game, based on cues such as home match and who won the last match. The take-the-best heuristic entails three steps to make such an inference: [9] Search rule: Look through cues in the order of their validity.