ACM Symposium on Applied Computing (SAC) 2027

A Technical Track on
Semantic Technology (ST)

ACM Symposium on Applied Computing

CALL FOR PAPERS

The Semantic Technology (ST) track invites original research and practical contributions that advance semantic technologies in the era of Generative AI, Large Language Models (LLMs), and intelligent agents. We particularly welcome work that integrates symbolic and semantic knowledge with modern AI to improve reasoning, grounding, explainability, interoperability, reliability, and knowledge-intensive applications. The scope includes Semantic Web technologies, ontologies, knowledge graphs, semantic data management and integration, neuro-symbolic AI, knowledge-enhanced LLMs, Retrieval-Augmented Generation (RAG), and semantic approaches to intelligent and agentic systems.

The track welcomes papers addressing theoretical foundations, novel methods, architectures, systems, benchmarks, and real-world applications. Topics of interest include, but are not limited to:

Ontology and Knowledge Graph Engineering: Learning, constructing, aligning, evolving, validating, and maintaining ontologies, knowledge graphs, and knowledge bases using symbolic, machine-learning, and generative AI methods.

Knowledge-Enhanced and Neuro-Symbolic AI: Integrating ontologies, knowledge graphs, reasoning, and semantic constraints with machine learning, deep learning, LLMs, multimodal models, and other foundation models.

Semantic Technologies for Generative and Agentic AI: Semantic grounding, knowledge-enhanced generation, RAG, knowledge-aware AI agents, semantic memory, tool and service discovery, planning, reasoning, and coordination in single- and multi-agent systems.

Semantic Data Management and Interoperability: Using semantic technologies and AI to support data integration, interoperability, metadata management, data governance, data quality, provenance, and heterogeneous or multimodal data management.

Trustworthy and Explainable AI: Semantic approaches to improving the factuality, transparency, explainability, provenance, verification, safety, and trustworthiness of AI systems, including methods for detecting and reducing hallucinations in generative AI.

Semantic Search and Knowledge Discovery: Semantic and AI-based approaches to search, information retrieval, question answering, recommendation, knowledge discovery, and conversational information access.

Semantic Architectures and Platforms: Architectures, frameworks, tools, and platforms that combine semantic technologies with AI, foundation models, and intelligent agents for knowledge-intensive applications.

Evaluation and Benchmarking: Methods, datasets, benchmarks, metrics, and empirical studies for evaluating semantic, knowledge-enhanced, neuro-symbolic, generative, and agentic AI systems.

We especially encourage submissions demonstrating the impact of semantic technologies in real-world and emerging application domains, including education and e-learning, business and enterprise systems, social networks, geographic information systems, healthcare and medical informatics, bioinformatics, cybersecurity, scientific discovery, legal informatics, digital government, and other knowledge-intensive domains.

Topics include, but are not limited to:

• Semantic interoperability and ontology-enabled interoperability across heterogeneous information resources
• Ontologies, taxonomies, folksonomies, and other semantic knowledge representations
• Ontology and knowledge-graph construction, learning, alignment, evolution, validation, and maintenance
• Knowledge bases, knowledge graphs, and knowledge-graph applications
• Schema mapping, matching, integration, and semantic data integration
• Semantic data management, metadata management, annotation, provenance, and governance
• Semantic search, information retrieval, information extraction, and question answering
• emantic personalization, user modeling, and recommender systems
• Reasoning, inference, and knowledge-based decision support
• Semantic Web technologies and linked data
• Natural language processing, text mining, and natural language understanding using semantic technologies
• Semantic knowledge discovery, visual analytics, and data analytics
• Deep learning and neural methods for semantic representation, reasoning, retrieval, and natural language processing
• Semantic Technology for Neuro-symbolic AI and the integration of symbolic knowledge with machine learning and deep learning
• Explainable, interpretable, and trustworthy AI using semantic technologies
• Semantic technologies for Privacy, security, fairness, and ethical considerations in semantic and AI-enabled systems
• Semantic technologies for Generative AI, foundation models, and Large Language Models (LLMs)
• Semantic technologies for Knowledge-enhanced LLMs and semantic grounding of generative AI
• Semantic technologies for Retrieval-Augmented Generation (RAG) using ontologies, knowledge graphs, and semantic retrieval
• LLMs for ontology engineering, knowledge-graph construction, semantic annotation, and knowledge discovery
• Semantic technologies for improving the factuality, reliability, provenance, and explainability of LLMs
• Semantic technologies for agentic AI, including knowledge-aware agents, semantic memory, reasoning, planning, tool discovery, and multi-agent systems
• Development, adaptation, evaluation, and benchmarking of LLMs and other foundation models for semantic applications
• Applications of LLMs and generative AI to natural language processing and knowledge-intensive tasks
• Semantic technologies for Human-AI interaction and semantic approaches to personalized and context-aware intelligent systems
• Semantic technologies for Ethical and societal implications of LLMs, generative AI, and semantic AI systems
• Semantic social networks and social informatics
• Geospatial semantics and semantic technologies for geographic information systems
• Semantic technologies for multimodal data and multimodal AI
• Applications of semantic technologies and AI in education and e-learning, e-business, social networks, geographic information systems, healthcare and medical informatics, bioinformatics, cybersecurity, scientific discovery, and legal informatics

SUBMISSION TYPES

• Original and unpublished research work
• Reports of innovative computing applications in sciences, engineering, and business areas
• Reports of successful technology transfer to new problem domains
• Reports of industrial experience and demos of new innovative systems

** Submission Policy

** Minimum Length for Review Consideration

Important update on ACMs new open access publishing model for 2027 ACM Conferences!

Each paper will be double-blindly reviewed by at least three reviewers; this is an ACM requirement as SAC is a “Refereed Conference”. Please adhere to this requirement when you prepare for your paper. Double-blindly means that the author of a paper does not know the reviewers of his/her paper and reviewers do not know the authors of the papers they reviewed.

By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all ACM Publications Policies, including ACM's new Publications Policy on Research Involving Human Participants and Subjects. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.

Please ensure that you and your co-authors obtain an ORCID ID, so you can complete the publishing process for your accepted paper. ACM has been involved in ORCID from the start and we have recently made a commitment to collect ORCID IDs from all of our published authors. We are committed to improve author discoverability, ensure proper attribution and contribute to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.

The same paper cannot be submitted to more than one track. All paper submissions MUST BE "Original, unpublished work."

Paper registration is required to allow the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM/IEEE digital library. No-show of scheduled papers and posters will result in exclusion from the ACM/IEEE digital library.

SUBMISSION PROCEDURES

RESEARCH PAPERS

• For accepted regular papers, full papers are limited to 8 pages with the option for up to 2 additional pages.
• For accepted poster papers, posters are limited to 2 pages with the option for up to 1 additional page.

STUDENT RESEARCH COMPETITION (SRC)

As before, SAC 2026 organizes a Student Research Competition (SRC) Program to allow graduate students to meet and exchange ideas with researchers and practitioners in their areas of interest. Student Research Abstracts are limited to 3 pages in ACM format using the posted template, no additional pages.

IMPORTANT DUE DATES

PROGRAM CHAIRS

PROGRAM COMMITTEE (To be added further)

Idir Amine Amarouche, USTHB/Bab Ezzouar, Algeria

Hajer Baazaoui, CY Cergy Paris University, France

Patrizio Bellan, Fondazione Bruno Kessler and Free University of Bozen-Bolzano, Italy

Carlos Bobed, University of Zaragoza, Spain

Loris Bozzato, Fondazione Bruno Kessler, Italy

Agustina Buccella, Universidad Nacional del Comahue, Argentina

Flavius Frasincar, Erasmus University Rotterdam, the Netherlands

James Geller, New Jersey Institute of Technology, USA

Sven Groppe, IFIS University of Lubeck, Germany

Miguel A. Martínez-Prieto, University of Valladolid, Spain

Tarmo Robal, Tallinn University of Technology, Estonia

Toky Raboanary, ISPM

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