Titlebook: Knowledge Discovery, Knowledge Engineering and Knowledge Management; 13th International J Ana Fred,David Aveiro,Joaquim Filipe Conference p

形上升才刺激

啞巴

協(xié)議

,Pathology Data Prioritisation: A Study of?Using Multi-variate Time Series Without a?Ground Truth, results to review on a single shift; this “information overload” presents a particular challenge. Some form of pathology result prioritisation is therefore a necessity. One idea to deal with this problem is to adopt the tools and techniques of machine learning to identify prioritisation patterns wi

流浪

,From Event Tracking to?Event Modelling: Understanding as?a?Paradigm Shift,ed that for algorithms to accomplish their task, to detect and track events in the news media accurately, they had to understand events. Yet it has taken event tracking the decades since then to resolve what it means to understand events and how. Simple interpretations of understanding often failed;

antecedence

鍍金

Multidimensional Fairness in Paper Recommendation,ies show that bias still exists. This implicit bias may persist when recommendation algorithms for paper selection are employed instead. To address this, we describe three fair algorithms that specifically take into account author diversity in paper recommendation. In contrast to fair algorithms tha

恃強凌弱

The Foundational Ontology ThingFO: Architectural Aspects, Concepts, and Applicability,e perceived or conceived world, including particular things (classes and individuals/instances), universal things (classes of classes), and assertions (expression classes) about both kinds of things and relations. Furthermore, ThingFO is placed at the top (foundational) level in the framework of a f

amyloid

Evidence in Policymaking: A Systematic Approach, tackle complex social problems. In this paper, we explore a methodology for a Decision Support System that could help policymakers cope and incorporate the problems’ complexity during the design and implementation of their policies. The methodology is based upon a systematic exploration of the prob

Obstacle

,BERT-Based Ensemble Learning Approach for?Sentiment Analysis,own great success in sentiment analysis and have been considered the state-of-the-art model for different NLP tasks. However, the accuracy of sentiment analysis for low resource Languages still needs improvements. In this paper, we are concerned with sentiment analysis for Arabic documents. We first

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