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Found 9 papers, 0 papers with code
Forecasting GDP in Europe with Textual Data
We evaluate the informational content of news-based sentiment indicators for forecasting Gross Domestic Product (GDP) and other macroeconomic variables of the five major European economies.
Forecasting with Economic News
The goal of this paper is to evaluate the informational content of sentiment extracted from news articles about the state of the economy.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
Neural Forecasting of the Italian Sovereign Bond Market with Economic News
In this paper we employ economic news within a neural network framework to forecast the Italian 10-year interest rate spread.
Emotions in Macroeconomic News and their Impact on the European Bond Market
We show how emotions extracted from macroeconomic news can be used to explain and forecast future behaviour of sovereign bond yield spreads in Italy and Spain.
Artificial Intelligence in Clinical Health Care Applications: Viewpoint
The idea of Artificial Intelligence (AI) has a long history.
Evolutionary Construction of Convolutional Neural Networks
It combines deep neural networks and evolutionary algorithms to improve and/or automate the construction of neural networks.
Towards an automated method based on Iterated Local Search optimization for tuning the parameters of Support Vector Machines
We provide preliminary details and formulation of an optimization strategy under current development that is able to automatically tune the parameters of a Support Vector Machine over new datasets.
An intelligent extension of Variable Neighbourhood Search for labelling graph problems
In this paper we describe an extension of the Variable Neighbourhood Search (VNS) which integrates the basic VNS with other complementary approaches from machine learning, statistics and experimental algorithmic, in order to produce high-quality performance and to completely automate the resulting optimization strategy.
Towards an intelligent VNS heuristic for the k-labelled spanning forest problem
In a currently ongoing project, we investigate a new possibility for solving the k-labelled spanning forest (kLSF) problem by an intelligent Variable Neighbourhood Search (Int-VNS) metaheuristic.
