Enriching Knowledge Bases with Counting Quantifiers

Information extraction traditionally focuses on extracting relations between identifiable entities, such as . Yet, texts often also contain Counting information, stating that a subject is in a specific relation with a number of objects, without mentioning the objects themselves, for example, "California is divided into 58 counties". Such counting quantifiers can help in a variety of tasks such as query answering or knowledge base curation, but are neglected by prior work. This paper develops the first full-fledged system for extracting counting information from text, called CINEX. We employ distant supervision using fact counts from a knowledge base as training seeds, and develop novel techniques for dealing with several challenges: (i) non-maximal training seeds due to the incompleteness of knowledge bases, (ii) sparse and skewed observations in text sources, and (iii) high diversity of linguistic patterns. Experiments with five human-evaluated relations show that CINEX can achieve 60% average precision for extracting counting information. In a large-scale experiment, we demonstrate the potential for knowledge base enrichment by applying CINEX to 2,474 frequent relations in Wikidata. CINEX can assert the existence of 2.5M facts for 110 distinct relations, which is 28% more than the existing Wikidata facts for these relations.Comment: 16 pages, The 17th International Semantic Web Conference (ISWC 2018

Numerical Key Performance Indicators for the Validation of PHM Health Indicators with Application to a Hydraulic Actuation System

In order to perform Prognostic and Health Management (PHM) of a given system, it is necessary to define some relevant variables sensitive to the different degradation modes of the system. Those variables are named Health Indicators (HI) and they are the keystone of PHM. However, they are subject to a lot of uncertainties when computed in real time and the stochastic nature of PHM makes it hard to evaluate the efficiency of a HI set before the extraction algorithm is implemented. This document introduces Numerical Key Performance Indicators (NKPI) for the validation of HI computed only from data provided by numerical models in the upstream stages of a PHM system development process. In order to match as good as possible the reality, the multiple sources of uncertainties are quantified and propagated into the model. After having introduced the issue of uncertain systems modeling, the different NKPI are defined and eventually an application is performed on a hydraulic actuation system of an aircraft engine

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

The system of tracking the position of the bucket excavator's wheel for prevention of risk situations

For companies doing business in mining mineral deposits, ensuring safe work is one of the key tasks (Safety First!). One of the important trends in this area is prevention and endeavour to forestall risk situations. Risks need to be searched, technically described, spatially defined, evaluated and categorized by degree of risk. Complex geological and stability conditions can be one of the sources of persistent and significant risks, which are mainly landslides and rockslides threatening both mining equipment and employees. The problem described in this article and its solution concerns the Most Basin (formerly the North Bohemian Lignite Basin). This is a tertiary basin that was founded in the Oligocene. The main mineral is lignite and mining takes place on the surface. The main excavating machinery in the surface lignite quarries in Europe (Czech Republic, Germany, Poland) is the bucket wheel excavator.Web of Science15328727