Semantic Computing and Web 3.0

Web 3.0 is an evolution from Web 2.0. At present it remains to be a concept and does not have a precise definition.

There are different ways to describe Web 3.0 at the conceptual level. Below are two typical ones:

(A) Source: http://www.labnol.org/internet/web-3-concepts-explained/8908/

“Web 1.0 – That Geocities & Hotmail era was all about read-only content and static HTML websites. People preferred navigating the web through link directories of Yahoo! and dmoz.

Web 2.0 – This is about user-generated content and the read-write web. People are consuming as well as contributing information through blogs or sites like Flickr, YouTube, Digg, etc. The line dividing a consumer and content publisher is increasingly getting blurred in the Web 2.0 era.

Web 3.0 – This will be about semantic web (or the meaning of data), personalization (e.g. iGoogle), intelligent search and behavioral advertising among other things. “

(B) Source: http://asmarterplanet.com/blog/2009/07/the-internet-of-things-or-web-30.html

“….if Web 1.0 was characterized by connecting people to content, and Web 2.0 is connecting people to people, then Web 3.0 is certainly connecting objects to people and to each other. The Internet of things.”

Semantic Computing is inline with both views. The “content” addressed in Semantic Computing is not restricted to traditional web content such as text, image and video, but also includes hardware, software, everything, as described in the second view. The inclusion of understanding user intentions and content semantics addresses intelligent search. Another point that may be important is that Semantic Computing encourages user engagement to better describe the semantics of intentions and content.

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).

Semantic Computing and Semantic Web

Semantic Web was introduced in the pioneering article of Tim Berners-Lee, James Hendler and Ora Lassila (Scientific American, 2001); it may be defined as “a highly interconnected network of data that could be easily accessed and understood by any desktop or handheld machine.” (in “The Semantic Web In Action”, by  Lee Feigenbaum, Ivan Herman, Tonya Hongsermeier, Eric Neumann and Susie Stephens, Scientific American, 2007). The vision of Semantic Web has resulted in the formation of W3C (World Wide Web Consortium, http://www.w3c.org).

We tried to define Semantic Computing to address the derivation and matching of the semantics of computational content to that of naturally expressed user intentions in order to retrieve, manage, manipulate or even create content, where “content” may be anything including video, audio, text, process, service, hardware, network, community, etc.

As an extension of Semantic Web, Semantic Computing considers the Internet as computational content that includes tools as well as data, and assumes they will continue to exist in their current forms (as HTML pages, online services, etc.)

In addition to web data, Semantic Computing considers all computational content that includes hardware, software, network, etc. Consider, for example, software (code) as content. Semantic Computing addresses the derivation and matching of the semantics of software (code) to that of naturally expressed user intentions to retrieve, manage, manipulate or create the software.  We may expand this into several subjects in Software Engineering. For example Requirements Engineering addresses the translation of user requirements that may be specified in natural language into a design specification.

Finally Semantic Computing specifically addresses the derivation of the semantics of naturally expressed user intentions, as I addressed in the last article. 

I think Semantic Web is an important part of Semantic Computing and many technologies developed for Semantic Web may be used for other fields (and vice versa). We  hope people from other fields such as Software Engineering can also join us so that we may be able to identify some common science and technologies that can facilitate the advances of all.

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).

What is Semantic Computing?

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).