High throughput discovery and characterization of tick and pathogen vaccine protective antigens using vaccinomics with intelligent Big Data analytic techniques
Introduction: The incidence of tick-borne diseases (TBDs) is growing worldwide, and
vaccines appear as the most effective and environmentally sound intervention for the …
vaccines appear as the most effective and environmentally sound intervention for the …
NaRuto: Automatically Acquiring Planning Models from Narrative Texts
Domain model acquisition has been identified as a bottleneck in the application of planning
technology, especially within narrative planning. Learning action models from narrative texts …
technology, especially within narrative planning. Learning action models from narrative texts …
Automated Action Model Acquisition from Narrative Texts
Action models, which take the form of precondition/effect axioms, facilitate causal and
motivational connections between actions for AI agents. Action model acquisition has been …
motivational connections between actions for AI agents. Action model acquisition has been …
Extracting answers from causal mechanisms in a medical document
The aim of this paper is to approach causal questions in medical documents eventually
recovered from a search engine. Causal questions par excellence are what, how and why …
recovered from a search engine. Causal questions par excellence are what, how and why …
Towards Learning Action Models from Narrative Text Through Extraction and Ordering of Structured Events
Event models, in the form of scripts, frames, or precondition/effect axioms, allow for
reasoning about the causal and motivational connections between events in a story, and …
reasoning about the causal and motivational connections between events in a story, and …
Imperfect causality: Combining experimentation and theory
A Sobrino - Combining Experimentation and Theory: A Hommage …, 2012 - Springer
This paper is a journey around causality, imperfect causality, causal models and
experiments for testing hypothesis about what causality is, with special attention to imperfect …
experiments for testing hypothesis about what causality is, with special attention to imperfect …
Creating a natural language summary from a compressed causal graph
The aim of this paper is to introduce a set of procedures capable of produce a text summary
from a causal graph. In previous works we have presented several algorithms to extract …
from a causal graph. In previous works we have presented several algorithms to extract …
[HTML][HTML] Summarizing information by means of causal sentences through causal graphs
The objective of this work is to propose a complete system able to extract causal sentences
from a set of text documents, select the causal sentences contained, create a causal graph …
from a set of text documents, select the causal sentences contained, create a causal graph …
Fake news detection by means of uncertainty weighted causal graphs
Society is experimenting changes in information consumption, as new information channels
such as social networks let people share news that do not necessarily be trust worthy …
such as social networks let people share news that do not necessarily be trust worthy …
Mining temporal causal relations in medical texts
Causal sentences are a main part of the medical explanations, providing the causes of
diseases or showing the effects of medical treatments. In medicine, causal association is …
diseases or showing the effects of medical treatments. In medicine, causal association is …