a relation type, and a superclass for every relation. Then, we will train three machine-learning models on this dataset: a support vector machine (SVM), a dense model (D-Model), and a convolutional neural networ
6.6.1 Introduction Relation extraction (RE) is a task seeking to extract structured information from unstructured artifacts. It has many applications, such as bio-text mining and named entity recognition. The relation is defined as a tuple t = (e1, e2, …, en), and the ei denotes the ent...
Structure having one associative operation with identity and inverses. Function f from one structure S to another structure T such that, for every operation * and all x, y in S, f(x * y) = f(x) * f(y). Ideal Subset I of a ring containing the sum and difference of any two eleme...
a relation type, and a superclass for every relation. Then, we will train three machine-learning models on this dataset: a support vector machine (SVM), a
Introduction Heisenberg’s uncertainty relation (HUR)1is one of the pillars of quantum mechanics and it sets the limit of how precisely one can predict the outcome of the measurements of two non-commuting observables. While the relation itself is a simple consequence of Born’s rule and the ...
and syntactic information about the entities, enabling the neural network to effectively process and learn from the input data while preserving contextual relationships between entities. Through the training process, the parameters of the embedding matrixWembare optimized to minimize the loss function, ...
Introduction Global conservation goals typically emphasize setting aside land for wildlife1. Protected areas (PAs) can serve as refuges from anthropogenic impacts, both direct (e.g., harvest, hunting) and indirect (e.g., habitat modification). While much research has been devoted to developing me...
1 Introduction Exponential, trigonometric and hyperbolic functions plays very important role in pure and applied mathematics. These functions are useful for handling many engineering and technological problems. Extension of these functions is very interesting area of latest developments. The Mittag-Leffler ...
By using a Haskell implementation of relation-algebraic primitives, we can implement the programs described in Section 3 with a single higher-order function that is parameterized over the rectangle computation. In Subsection 4.1 we present such an implementation and discuss the running time complexity ...
1. Introduction Knowledge Graph (KG) is a technology that can store relational facts in the form of triples. For example, “The Eiffel Tower is located in Paris” can be represented as a machine-readable triple (The Eiffel Tower, locatedIn, Paris) in a knowledge graph. Knowledge graphs are...