JOURNAL ARTICLE

Workshop on Enterprise Knowledge Graphs using Large Language Models

Abstract

Knowledge graphs are used for organizing and connecting individual entities to integrate the information extracted from different data sources. Typically, knowledge graphs are used to connect various real-world entities like persons, places, things, actions, etc. For the knowledge graphs created using the enterprise data, the knowledge graph entities can be of different types-static entities (e.g., people, projects), communication entities (e.g., emails, meetings, documents), derived entities (e.g., rules, definitions, entities from emails), etc. The graphs are used to connect these entities with enriched context (as edges and node attributes) and used for powering various search and recommendations applications.

Keywords:
Knowledge graph Computer science Context (archaeology) Conceptual graph Graph Node (physics) World Wide Web Data science Information retrieval Knowledge representation and reasoning Theoretical computer science Artificial intelligence Engineering

Metrics

2
Cited By
0.51
FWCI (Field Weighted Citation Impact)
0
Refs
0.67
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Graph Neural Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Service-Oriented Architecture and Web Services
Physical Sciences →  Computer Science →  Information Systems
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