My Account Log in

1 option

Formal Methods for the Analysis of Biomedical Ontologies / by Guo-Qiang Zhang, Rashmie Abeysinghe, Licong Cui.

Springer Nature Synthesis Collection of Technology Collection 11 Available online

View online
Format:
Book
Author/Creator:
Zhang, Guo-Qiang, author.
Abeysinghe, Rashmie, author.
Cui, Licong, author.
Series:
Synthesis Lectures on Data, Semantics, and Knowledge, 2691-2031
Language:
English
Subjects (All):
Information retrieval.
Computer architecture.
Data structures (Computer science).
Information theory.
Artificial intelligence--Data processing.
Artificial intelligence.
Medicine--Research.
Medicine.
Biology--Research.
Biology.
Ontology.
Data Storage Representation.
Data Structures and Information Theory.
Data Science.
Biomedical Research.
Local Subjects:
Data Storage Representation.
Data Structures and Information Theory.
Data Science.
Biomedical Research.
Ontology.
Physical Description:
1 online resource (258 pages)
Edition:
1st ed. 2022.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2022.
Summary:
The book synthesizes research on the analysis of biomedical ontologies using formal concept analysis, including through auditing, curation, and enhancement. As the evolution of biomedical ontologies almost inevitably involves manual work, formal methods are a particularly useful tool for ontological engineering and practice, particularly in uncovering unexpected "bugs" and content materials. The book first introduces simple but formalized strategies for discovering undesired and incoherent patterns in ontologies before exploring the application of formal concept analysis for semantic completeness. The book then turns to formal concept analysis, a classical approach used in the mathematical treatment of orders and lattices, as an ontological engineering principle, focusing on the structural property of ontologies with respect to its conformation to lattice or not (non-lattice). The book helpfully covers the development of more efficient algorithms for non-lattice detection and extraction required by exhaustive lattice/non-lattice analysis. The book goes on to highlight the power and utility of uncovering non-lattice structure for debugging ontologies and describes methods that leverage the linguistic information in concept names (labels) for ontological analysis. It also addresses visualization and performance evaluation issues before closing with an overview and forward-looking perspectives on the field. This book is intended for graduate students and researchers interested in biomedical ontologies and their applications. It can be a useful supplement for courses on knowledge representation and engineering and also provide readers with a reference for related scientific publications and literature to assist in identifying potential research topics. All mathematical concepts and notations used in this book can be found in standard discrete mathematics textbooks, and the appendix at the end of the book provides a list of keyontological resources, as well as annotated non-lattice and lattice examples that were discovered using the authors' methods, demonstrating how "bugs are fixed" by converting non-lattices to lattices with minimal edit changes.
Contents:
Introduction
Simple Relational Patterns
Formal Concept Analysis and Semantic Completeness
Algorithms for Extracting Non-lattice Substructures
Non-lattice Substructures in Ontological Analysis
Lexical Sequences and Patterns
Visualization and Retrospective Ground-Truthing
Conclusion.
Notes:
Includes bibliographical references.
Other Format:
Print version: Zhang, Guo-Qiang Formal Methods for the Analysis of Biomedical Ontologies
ISBN:
3-031-12131-7
OCLC:
1350690238

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account