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008			220131s2022 sz | s |||| 0|eng d
020			_a9783030954819
024	7		_a10.1007/978-3-030-95481-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ334 _b2022 EB
245	1	0	_aReasoning Web. Declarative Artificial Intelligence : _b17th International Summer School 2021, Leuven, Belgium, September 8-15, 2021, Tutorial Lectures _cedited by Mantas Šimkus, Ivan Varzinczak
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (IX, 185 páginas) _b33 ilustraciones, 9 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aInformation Systems and Applications incl. Internet/Web and HCI _v13100
505	0		_aFoundations of Graph Path Query Languages -- On Combining Ontologies and Rules -- Modelling Symbolic Knowledge using Neural Representations -- Mining the Semantic Web with Machine Learning: main issues that need to be known -- Temporal ASP: from logical foundations to practical use with telingo -- A Review of SHACL: From Data Validation to Schema Reasoning for RDF Graphs -- Score-Based Explanations in Data Management and Machine Learning: An Answer-Set Programming Approach to Counterfactual Analysis.
520			_aThe purpose of the Reasoning Web Summer School is to disseminate recent advances on reasoning techniques and related issues that are of particular interest to Semantic Web and Linked Data applications. It is primarily intended for postgraduate students, postdocs, young researchers, and senior researchers wishing to deepen their knowledge. As in the previous years, lectures in the summer school were given by a distinguished group of expert lecturers. The broad theme of this year's summer school was again "Declarative Artificial Intelligence" and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures were presented during the school: Foundations of Graph Path Query Languages; On Combining Ontologies and Rules; Modelling Symbolic Knowledge Using Neural Representations; Mining the Semantic Web with Machine Learning: Main Issues That Need to Be Known; Temporal ASP: From Logical Foundations to Practical Use with telingo; A Review of SHACL: From Data Validation to Schema Reasoning for RDF Graphs; and Score-Based Explanations in Data Management and Machine Learning.
988			_aSpringer_Computer_2022
650		7	_2embne _aInteligencia artificial _vCongresos y asambleas _9413115
700	1		_aŠimkus, Mantas _eeditor literario _0(orcid)0000-0003-0632-0294 _1https://orcid.org/0000-0003-0632-0294 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aVarzinczak, Ivan _eeditor literario _0(orcid)0000-0002-0025-9632 _1https://orcid.org/0000-0002-0025-9632 _4edt _4http://id.loc.gov/vocabulary/relators/edt
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030954802
776	0	8	_iPrinted edition: _z9783030954826
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-95481-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2022 _dz _eh _zSI