Search results
Results From The WOW.Com Content Network
[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 ...
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.
Textual entailment can be illustrated with examples of three different relations: [5] An example of a positive TE (text entails hypothesis) is: text: If you help the needy, God will reward you. hypothesis: Giving money to a poor man has good consequences. An example of a negative TE (text contradicts hypothesis) is:
These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus . Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence.
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.
Children can make the distinction between mass and count nouns based on the article that precedes a new word. If a new word immediately follows the article a, then children infer that the noun is a count noun. If a new word immediately follows some, then the new word is inferred as a mass noun. [23]
Each logic operator can be used in an assertion about variables and operations, showing a basic rule of inference. Examples: The column-14 operator (OR), shows Addition rule: when p=T (the hypothesis selects the first two lines of the table), we see (at column-14) that p∨q=T.