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For example, a map might contain keys representing every unique word in a text and values representing the number of times that word appears in the text. A set is simply an ascending container of unique elements. As stated earlier, map and set only allow one instance of a key
The word embedding approach is able to capture multiple different degrees of similarity between words. Mikolov et al. (2013) [26] found that semantic and syntactic patterns can be reproduced using vector arithmetic. Patterns such as "Man is to Woman as Brother is to Sister" can be generated through algebraic operations on the vector ...
Polyinstantiation in computer science is the concept of type (class, database row or otherwise) being instantiated into multiple independent instances (objects, copies). It may also indicate, such as in the case of database polyinstantiation, that two different instances have the same name (identifier, primary key).
For instance, consider "SELECT name from Student". In the case that there are multiple records with name "Sara" in the student table, all of them are shown. That means the result of an SQL query is a multiset; if the result were instead a set, the repetitive records in the result set would have been eliminated.
The type–token distinction separates types (abstract descriptive concepts) from tokens (objects that instantiate concepts). For example, in the sentence "the bicycle is becoming more popular" the word bicycle represents the abstract concept of bicycles and this abstract concept is a type, whereas in the sentence "the bicycle is in the garage", it represents a particular object and this ...
This set of words contains many expressions that turn out to denote equal values in every lattice. For example, if a is some element of X , then a ∨ 1 = 1 and a ∧ 1 = a . The word problem for free bounded lattices is the problem of determining which of these elements of W ( X ) denote the same element in the free bounded lattice FX , and ...
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Instead of receiving a set of instances which are individually labeled, the learner receives a set of labeled bags, each containing many instances. In the simple case of multiple-instance binary classification, a bag may be labeled negative if all the instances in it are negative. On the other hand, a bag is labeled positive if there is at ...