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_9978-3-031-31414-8
024 7 _a10.1007/978-3-031-31414-8
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245 1 0 _aReasoning Web. Causality, Explanations and Declarative Knowledge
_h[electronic resource] :
_b18th International Summer School 2022, Berlin, Germany, September 27–30, 2022, Tutorial Lectures /
_cedited by Leopoldo Bertossi, Guohui Xiao.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aIX, 211 p. 22 illus., 15 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v13759
505 0 _aExplainability in Machine Learning -- Causal Explanations and Fairness in Data -- Statistical Relational Extensions of Answer Set Programming -- Vadalog: Its Extensions and Business Applications -- Cross-Modal Knowledge Discovery, Inference, and Challenges -- Reasoning with Tractable Probabilistic Circuits -- From Statistical Relational to Neural Symbolic Artificial Intelligence -- Building Intelligent Data Apps in Rel using Reasoning and Probabilistic Modelling.
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 “Reasoning in Probabilistic Models and Machine Learning” 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: Logic-Based Explainability in Machine Learning; Causal Explanations and Fairness in Data; Statistical Relational Extensions of Answer Set Programming; Vadalog: Its Extensions and Business Applications; Cross-Modal Knowledge Discovery, Inference, and Challenges; Reasoning with Tractable Probabilistic Circuits; From Statistical Relational to Neural Symbolic Artificial Intelligence; Building Intelligent Data Apps in Rel using Reasoning and Probabilistic Modelling.
650 0 _aApplication software.
650 1 4 _aComputer and Information Systems Applications.
700 1 _aBertossi, Leopoldo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aXiao, Guohui.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031314131
776 0 8 _iPrinted edition:
_z9783031314155
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v13759
856 4 0 _uhttps://doi.org/10.1007/978-3-031-31414-8
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