The field of Semantic Computing (SC) was introduced by Phillip Sheu in 2007 with the launch of the IEEE International Conference on Semantic Computing (ICSC) and the International Journal of Semantic Computing (IJSC). As articulated in the inaugural issue of IJSC, “the field of Semantic Computing addresses computing technologies, and their interactions, that can be used to extract or process the contents and semantics of active services and passive data that are unstructured, semi-structured, as well as structured.” It extends the Semantic Web—traditionally focused on ontology-based augmentation of web pages—both in breadth, by incorporating multimedia, services, and structured data beyond the web, and in depth, by addressing the access, use, synthesis, integration, and analysis of data and services. In doing so, Semantic Computing unifies diverse areas such as software engineering, user interfaces, natural language processing, artificial intelligence, programming languages, grid computing, and pervasive computing within a coherent framework.

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This vision is realized through a multi-layered architectural model designed to process, integrate, and utilize semantic information. The original framework consists of four layers: Semantic Analysis, which interprets signals such as pixels and words to extract meaning; Semantic Integration, which consolidates content and semantics from heterogeneous sources; Applications, which leverage this semantic content to address specific tasks and may provide services to other applications; and the Semantic Interface, which enables users to access and manipulate semantic content across sources. This architecture was subsequently refined into a five-layer model, in which the Applications layer was divided into Semantic Services—focused on solving specific problems through capabilities such as web search, question answering, content-based multimedia retrieval, and semantic synthesis—and Service Integration, which orchestrates multiple semantic services to deliver more comprehensive and interoperable solutions.

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Recent developments in Semantic Computing are advancing toward the science and engineering of reliable generative problem-solving systems—systems that bring together semantic understanding, generative AI, classical AI, knowledge, algorithms, tools, and verification to generate, solve, and validate solutions to complex real-world problems.

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1. Message from General Chairs". International Conference on Semantic Computing (ICSC 2007). 2007. pp. xiv. doi:10.1109/ICSC.2007.4. ISBN 978-0-7695-2997-4.

2. Sheu, Phillip C.-Y. (2007). "Editorial preface". International Journal of Semantic Computing. 01 (1): 1 9. doi:10.1142/S1793351X07000068. ISSN 1793-351X.

3. Sheu, Phillio C.-Y.; Ramaoorthy, C. V. (2009). "Problems, Solutions, and Semantic Computing". International Journal of Semantic Computing. 03 (3): 383–394. doi:10.1142/s1793351x09000781. ISSN 1793-351X.

4. Florian Schimanke, Mustafa Sert, and Chung-Hsien (eds), Semantic Computing and AI, World Scientiic Publishing, 2025

5. Hsiang-Shun Shih, Chengheng Lyu, Goli Vaisi, Phillip C-Y Sheu, "Generative Problem Solving," Proceedings, International Conference on Semantic Computing (ICSC 2025) (PDF)

6. 20th anniversary special issue, International Journal of Semantic Computing, 2026 (to appear)