<?xml version="1.0" encoding="UTF-8"?>
<mods xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.loc.gov/mods/v3" version="3.1" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
  <titleInfo>
    <title>Symbolic and Quantitative Approaches to Reasoning with Uncertainty</title>
    <subTitle>17th European Conference, ECSQARU 2023, Arras, France, September 19–22, 2023, Proceedings</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Bouraoui, Zied.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">edt</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">http://id.loc.gov/vocabulary/relators/edt</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Vesic, Srdjan.</namePart>
    <role>
      <roleTerm type="text">editor.</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">edt</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">http://id.loc.gov/vocabulary/relators/edt</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>SpringerLink (Online service)</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">sz</placeTerm>
    </place>
    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">electronic</form>
    <form authority="gmd">electronic resource</form>
    <reformattingQuality>access</reformattingQuality>
    <extent>XX, 476 p. 89 illus., 62 illus. in color. online resource.</extent>
  </physicalDescription>
  <abstract>This book constitutes the refereed proceedings of the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2023, held in Arras, France, in September 2023. The 35 full papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers are organized in topical sections about Complexity and Database Theory; Formal Concept Analysis: Theoretical Advances; Formal Concept Analysis: Applications; Modelling and Explanation; Semantic Web and Graphs; Posters.</abstract>
  <tableOfContents>Complexity and Database Theory -- Functional Dependencies with Predicates: What Makes the g3-error Easy to Compute?  -- Formal Concept Analysis: Theoretical Advances -- Squared symmetric formal contexts and their connections with correlation matrices -- Aggregation Functions and Extent Structure Preservation in Formal Concept Analysis -- On pseudointents in Fuzzy Formal Concept Analysis -- Maximal Ordinal Two-Factorizations -- A Note on the Number of (Maximal) Antichains in the Lattice of set Partitions -- Formal Concept Analysis: Applications -- Formal Concept Analysis for Trace Clustering in Process Mining -- Summarization of massive RDF graphs using identifier classification -- Towards a Flexible and Scalable Data Stream Algorithm in FCA -- Modelling and Explanation Postmodern Human-Machine Dialogues: a Pedagogical Inquiry Experiment -- Conceptual Modelling with Euler+ Diagrams -- Automatic Textual Explanations of Concept Lattices -- Semantic Web and Graphs -- Ontology Population from French Classified Ads -- Graph Extraction for Assisting Crash Simulation Data Analysis -- Factorization of formal contexts from modal operators -- Towards confirmation measures to mixed attribute implications -- Concept lattices as a reduction tool for fuzzy relation equations -- Analysis of Slovak Court Decisions by Formal Concept Analysis and Machine Learning Methods.</tableOfContents>
  <note type="statement of responsibility">edited by Zied Bouraoui, Srdjan Vesic.</note>
  <subject authority="lcsh">
    <topic>Artificial intelligence</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Software engineering</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Machine theory</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Application software</topic>
  </subject>
  <subject>
    <topic>Artificial Intelligence</topic>
  </subject>
  <subject>
    <topic>Software Engineering</topic>
  </subject>
  <subject>
    <topic>Formal Languages and Automata Theory</topic>
  </subject>
  <subject>
    <topic>Computer and Information Systems Applications</topic>
  </subject>
  <classification authority="lcc">Q334-342</classification>
  <classification authority="lcc">TA347.A78</classification>
  <relatedItem type="host">
    <titleInfo>
      <title>Springer Nature eBook</title>
    </titleInfo>
  </relatedItem>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="series">
    <titleInfo>
      <title>Lecture Notes in Artificial Intelligence, 14294</title>
    </titleInfo>
  </relatedItem>
  <identifier type="isbn">9783031456084</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-45608-4</identifier>
  <location>
    <url>https://doi.org/10.1007/978-3-031-45608-4</url>
  </location>
  <recordInfo>
    <recordCreationDate encoding="marc">231118</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251030110834.0</recordChangeDate>
    <recordIdentifier source="DE-He213">978-3-031-45608-4</recordIdentifier>
  </recordInfo>
</mods>
