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Knowledge Management


Two minutes NLP -- Quick Intro to Knowledge Base Question Answering

#artificialintelligence

Knowledge base question answering (KBQA) aims to answer a natural language question over a knowledge base (KB) as its knowledge source. A knowledge base (KB) is a structured database that contains a collection of facts in the form subject, relation, object, where each fact can have properties attached called qualifiers. For example, the sentence "Barack Obama got married to Michelle Obama on 3 October 1992 at Trinity United Church" can be represented by the tuple Barack Obama, Spouse, Michelle Obama, with the qualifiers start time 3 October 1992 and place of marriage Trinity United Church . Popular knowledge bases are DBpedia and WikiData. Early works on KBQA focused on simple question answering, where there's only a single fact involved.


CERN's impact on medical technology

#artificialintelligence

This article was originally published in the July/August edition of CERN Courier magazine. Today, the tools of experimental particle physics are ubiquitous in hospitals and biomedical research. Particle beams damage cancer cells; high-performance computing infrastructures accelerate drug discoveries; computer simulations of how particles interact with matter are used to model the effects of radiation on biological tissues; and a diverse range of particle-physics-inspired detectors, from wire chambers to scintillating crystals to pixel detectors, all find new vocations imaging the human body. CERN has actively pursued medical applications of its technologies as far back as the 1970s. At that time, knowledge transfer happened – mostly serendipitously – through the initiative of individual researchers.


Knowledge-based Entity Prediction for Improved Machine Perception in Autonomous Systems

#artificialintelligence

For example, consider the case where the perception module detects a pedestrian (PCV) on the road. It does not, however, recognize that the pedestrian is jaywalking. Even if no jaywalking events have been seen while training the CV perception module, representing knowledge of this event – i.e. (Pedestrian, participatesIn, Jaywalking) – in the scene KG could provide a new insight or cue for handling this edge-case with KEP (i.e.


MobiGuide

Communications of the ACM

The trend for an aging population, which is typical for Europe and for other high-income regions, brings with it a sharp increase in the number of chronic patients and a shortage of clinicians and hospital beds. Evidence-based clinical decision-support systems are one of the promising solutions for this problem.15 In the 1990s, different research groups started to develop computer-interpretable clinical guidelines (CIGs)7 as a form of evidence-based decision-support systems (DSS). Narrative evidence-based clinical guidelines, focused on a single disease, and containing recommendations for the disease diagnosis and management, were manually represented in CIG formalisms, such as Asbru,11 GLIF,1 or PROforma.3 The CIGs formed a network of clinical decisions and actions and served as a knowledge base.


Create graphics, logos, and more without the Adobe learning curve

Mashable

TL;DR: A lifetime subscription to Drawtify Online Vector Graphic Editor is 91% down from its value of $899 -- get it as of Feb. 25 for just $79.99. It's no secret that Adobe's popular graphic design software has a learning curve. It can easily discourage new digital artists from the get-go. Drawtify is a graphic software similar to Adobe Illustrator or Photoshop, except it's designed to be more user-friendly. Plus, it requires no monthly or annual subscription fees -- just a single initial payment for a lifetime of use.


Human-Centered Approach to Static-Analysis-Driven Developer Tools

Communications of the ACM

They can be too opaque, and to raise the signal of what is most important, they end up hiding too much. "The purpose of abstraction is not to be vague, but to create a new semantic level in which one can be absolutely precise."--


OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines

arXiv.org Artificial Intelligence

We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-quality dose predictions from 19 KBP models that were developed by different research groups during the OpenKBP Grand Challenge. The dose predictions were input to four optimization models to form 76 unique KBP pipelines that generated 7600 plans. The predictions and plans were compared to the reference plans via: dose score, which is the average mean absolute voxel-by-voxel difference in dose a model achieved; the deviation in dose-volume histogram (DVH) criterion; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50 to 0.62, which indicates that the quality of the predictions is generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P<0.05; one-sided Wilcoxon test) on 18 of 23 DVH criteria. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for a conventional planning model. This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. In the interest of reproducibility, our data and code is freely available at https://github.com/ababier/open-kbp-opt.


Learning curve effect on the global variable renewable energy deployment

#artificialintelligence

The traditional electricity market in the world was dominated by fossil fuel technologies. Today renewable energy technologies, particularly VRE, are cheaper than fossil fuels in most countries of the world. The large-scale deployment of solar and wind generation in the past decade has led to a paradigm shift in the power system and electricity markets. How the deployment of VRE and other renewable energy technologies changes the dynamics of merit order and the marginal cost of electricity generation is present in this story. In this article, I discussed the trend of renewable energy and VRE from a global perspective.


Arenas

AAAI Conferences

In this paper, we study the problem of exchanging knowledge between a source and a target knowledge base (KB), connected through mappings. Differently from the traditional database exchange setting, which considers only the exchange of data, we are interested in exchanging implicit knowledge. As representation formalism we use Description Logics (DLs), thus assuming that the source and target KBs are given as a DL TBox ABox, while the mappings have the form of DL TBox assertions. We study the problem of translating the knowledge in the source KB according to these mappings. We define a general framework of KB exchange, and address the problems of representing implicit source information in the target, and of computing different kinds of solutions, i.e., target KBs with specified properties, given a source KB and a mapping.


Salayandia

AAAI Conferences

MetaShare is a knowledge-based system that supports the creation of data management plans and provides the functionality to support researchers as they implement those plans. MetaShare is a community-based, user-driven system that is being designed around the parallels of the scientific data life cycle and the development cycle of knowledge-based systems. MetaShare will provide recommendations and guidance to researchers based on the practices and decisions of similar projects. Using formal knowledge representation in the form of ontologies and rules, the system will be able to generate data collection, dissemination, and management tools to facilitate tasks with respect to using and sharing scientific data. MetaShare, which is initially targeting the research community at the University of Texas at El Paso, is being developed on a Web platform, using Semantic Web technologies. This paper presents a roadmap for the development of MetaShare, justifying the functionality and implementation decisions. In addition, the paper presents an argument concerning the return on investment for researchers and the planned evaluation for the system.