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Found 6 papers, 0 papers with code
Automatic detection of relevant information, predictions and forecasts in financial news through topic modelling with Latent Dirichlet Allocation
Financial news items are unstructured sources of information that can be mined to extract knowledge for market screening applications.
Detection of Temporality at Discourse Level on Financial News by Combining Natural Language Processing and Machine Learning
Therefore, understanding the temporality of the key statements in a text is essential to separate context information from valuable predictions.
Automatic explanation of the classification of Spanish legal judgments in jurisdiction-dependent law categories with tree estimators
This is the first work on automatic analysis of legal texts combining NLP and ML along with Explainable Artificial Intelligence techniques to automatically make the models' decisions understandable to end users.
Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages
To the best of our knowledge, no prior work in the literature has addressed this problem despite its practical interest in decision-making, and we are not aware of any previous NLP nor online Machine Learning approaches to TABEA.
Detection of financial opportunities in micro-blogging data with a stacked classification system
Specifically, we seek a high detection precision to present a financial operator a substantial amount of such tweets while differentiating them from the rest of financial emotions in our system.
Entertainment chatbot for the digital inclusion of elderly people without abstraction capabilities
Many of them relieve their loneliness with traditional media such as TV and radio, which are known to create a feeling of companionship.
