The task of knowledge graph construction presents a confounding challenge for statistical relational models. While the uncertainty of extractions from NLP tools and the ontological structure of knowledge are a perfect match for the strengths of statistical relational techniques, the vast and continually growing evidence from which knowledge graphs are constructed can make such models prohibitiv...

This short review will focus on how to interpret variants of uncertain significance (VUS) in the setting newborn screening (NBS) for severe combined immunodeficiency (SCID). Many tenets this can be extrapolated other settings; however, NBS SCID represents a best-case scenario variant interpretation because nearly all genes are known and phenotype is easily defined, usually as T-cell count. The ...

How do reasoning systems that learn evolve over time? Characterizing the evolution of these systems is important for understanding their limitations and gaining insights into the interplay between learning and reasoning. We describe an inverse ablation model for studying how learning and reasoning interact: Create a small knowledge base by ablation, and incrementally re-add facts, collecting sn...

The report presents an investigation of the ontology learning problem. It presents an overview of ontology research field and the discussion of available machine learning techniques and learning problems that arise in ontology learning. Recently appeared Web-based and Business-to-Business ontologies forced new learning problems to appear that are also presented in the report. Introduction The i...

The purpose of text clustering in information retrieval is to discover groups of semantically related documents. Accurate and comprehensible cluster descriptions (labels) let the user comprehend the collection’s content faster and are essential for various document browsing interfaces. The task of creating descriptive, sensible cluster labels is difficult—typical text clustering algorithms focu...

As an unsupervised learning process, document clustering has been used to improve information retrieval performance by grouping similar documents and to help text mining approaches by providing a high-quality input for them. In this article, the authors propose a novel hybrid clustering technique that incorporates semantic smoothing of document models into a neural network framework. Recently, ...

How do reasoning systems that learn evolve over time? What are the properties of different learning strategies? Characterizing the evolution of these systems is important for understanding their limitations and gaining insights into the interplay between learning and reasoning. We describe an inverse ablation model for studying how large knowledge-based systems evolve: Create a small knowledge ...

With more than 430 genetic defects, primary immunodeficiencies (PIDs) or inborn errors of immunity are a heterogeneous group rare disorders affecting the immune system.1Tangye S.G. Al-Herz W. Bousfiha A. Chatila T. Cunningham-Rundles C. Etzioni et al.Human immunity: 2019 update on classification from International Union Immunological Societies Expert Committee.J Clin Immunol. 2020; 40: 24-64Cro...

This study develops and tests a model of followers' attribution of charismatic qualities to their leader. The model stipulates that, leaders' visions being equal, followers' attributions of charisma to their leader will be determined by their leader's individual attributes and situational contexts. Specifically, this study theorizes that leaders' attributes, such as competence and sacrifice, be...

This paper describes a system being developed to identify Internet WWW pages that most closely respond to a users' requirements. The system is designed to enhance, rather than replace existing search engines. It collects pages identified by the search engine, and then uses an external lexical thesaurus to analyse their contents. This provides a secondary ordering metric for the pages based on a...