Semantic Computing is a computer term. It addresses the derivation and matching of the semantics of computational content to that of naturally expressed user intentions in order to satisfy the user. The term “content” may be interpreted broadly to include almost everything such as video, audio, text, process, service, hardware, network, community, etc.
What does Semantic Computing mean to users? One way to look at it is NATURAL LANGUAGE driven computing – You use natural language to interact with your computer, your cellphone, your car, everything.
To understand user intentions is not a trivial task; to satisfy the intentions is even more difficult. Consider, for example, a query “Plan a round-trip from New York to Europe, including at least Paris and London, in September for two weeks with less than $3,000.” It is easy to say, but involves a lot to understand and solve. First the computer has to parse your request, linking different linguistic components into a complete interpretation; it then need to check out the options for flights, hotels, local transportations, etc. (Just imagine how complicated it is for you to solve the problem.)
Natural language driven computing does not necessarily mean it is voice based, which is another technically challenge. Natural language queries may as well be typed.
Other components of Semantic Computing include for example Semantic Analysis, which analyzes content with the goal of converting it to machine processable semantics, and Semantic Integration, which integrates content and semantics from multiple sources. They are far more technical and transparent to the user.
The definition of Semantic Computing is evolving. I will make more attempts to explain what Semantic Computing is from different angles.
About the Author
Dr. Phillip C-Y. Sheu is currently a professor of EECS and Biomedical Engineering at the University of California, Irvine. He also serves as the Founding Director of the Institute for Semantic Computing, an international research organization that connects industry, government and academia to promote semantic computing technologies. He received his Ph.D. and M.S. degrees from the University of California at Berkeley in Electrical Engineering and Computer Science in 1986 and 1982, respectively. He has published more than 100 papers in object-relational data and knowledge engineering and their applications. His current research interests include semantic computing and complex biomedical systems. He is a Fellow of IEEE, the founding editor-in-Chief of the International Journal of Semantic Computing, and a primary author of the book Semantic Computing (Wiley, 2010).
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