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020			_a9783031121319
024	7		_a10.1007/978-3-031-12131-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aR858 _b2022 EB
100	1		_aZhang, Guo-Qiang, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686936 _d1960-
245	1	0	_aFormal Methods for the Analysis of Biomedical Ontologies _cby Guo-Qiang Zhang, Rashmie Abeysinghe, Licong Cui
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIV, 245 páginas) _b119 ilustraciones, 52 ilustraciones en blanco y negro
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Data Semantics and Knowledge _x2691-2031
505	0		_aIntroduction -- 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.
520			_aThe 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 key ontological 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.
988			_aSynthesis Collection of Technology_2022
650		7	_2embne _9421154 _aInformática médica
650		7	_2embne _9686599 _aOntologías (Recuperación de la información)
700	1		_aAbeysinghe, Rashmie _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686937
700	1		_aCui, Licong _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686938
776	0	8	_iPrinted edition: _z9783031121302
776	0	8	_iPrinted edition: _z9783031121326
776	0	8	_iPrinted edition: _z9783031121333
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-12131-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eIG _zSI