Atjaunināt sīkdatņu piekrišanu

E-grāmata: Knowledge Engineering and Knowledge Management: 24th International Conference, EKAW 2024, Amsterdam, The Netherlands, November 26-28, 2024, Proceedings

Edited by , Edited by , Edited by , Edited by , Edited by
  • Formāts: PDF+DRM
  • Sērija : Lecture Notes in Computer Science 15370
  • Izdošanas datums: 22-Nov-2024
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783031777929
  • Formāts - PDF+DRM
  • Cena: 77,31 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
  • Formāts: PDF+DRM
  • Sērija : Lecture Notes in Computer Science 15370
  • Izdošanas datums: 22-Nov-2024
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783031777929

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This book constitutes the refereed proceedings of the 24th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2024, held in Amsterdam, The Netherlands, during November 2628, 2024.





The 28 full papers presented together were carefully reviewed and selected from 115 submissions. They focus on all aspects of knowledge in constructing systems and services for the semantic web, knowledge management, knowledge discovery, information integration, natural language processing, intelligent systems, e-business, e-health, humanities, cultural heritage, and beyond.

.- Examining LGBTQ+-related Concepts in the Semantic Web: Link Discovery, Concept Drift, Ambiguity, and Multilingual Information Reuse.
.- Capturing the Viewpoint Dynamics in the News Domain.
.- Influence beyond similarity: A Contrastive Learning approach to Object Influence Retrieval.
.- Discovering a Representative Set of Link Keys in RDF Datasets.
.- Understanding the impact of entity linking on the topology of entity co-occurrence networks for social media analysis.
.- Empowering CamemBERT Legal Entity Extraction With LLM Boostrapping.
.- Lexicalization Is All You Need: Examining the Impact of Lexical Knowledge in a Compositional QALD System.
.- On the Roles of Competency Questions in Ontology Engineering.
.- Structured Representations for Narratives.
.- Comparing Symbolic and Embedding-Based Approaches for Relational Blocking.
.- UniQ-Gen: Unified Query Generation across Multiple Knowledge Graphs.
.- LLM-Driven Knowledge Extraction in Temporal and Description Logics.
.- FAVEL: Fact Validation Ensemble Learning.
.- A Framework for Evaluating Entity Alignment Impact on Downstream Knowledge Discovery.
.- Scholarly Wikidata: Population and Exploration of Conference Data in Wikidata using LLMs.
.- Understanding inflicted injuries in young children: Toward an ontology based approach.
.- A Review and Comparison of Competency Question Engineering Approaches.
.- A generic framework to better understand and compare FAIRness measures.
.- ORKA: An Ontology for Robotic Knowledge Acquisition.
.- Transformers in the Service of Description Logic-based Contexts.
.- Additive Counterfactuals for Explaining Link Predictions on Knowledge Graphs.
.- PeGazUs: A knowledge graph based approach to build urban perpetual gazetteers.
.- Ontology-Constrained Generation of Domain-Specific Clinical Summaries.
.- Contextualizing Entity Representations for Zero-Shot Relation Extraction with Masked Language Models.
.- Validating a Functional Status Knowledge Graph in a Large-scale Living Lab.
.- Human Evaluation of Procedural Knowledge Graph Extraction from Text with Large Language Models.
.- Modelling and Mining Knowledge about Computational Complexity.
.- Generating a Question Answering Dataset about Geographic Changes in a Knowledge Graph.