Prof. Wolfgang Wahlster
Semantic Web: It’s All in the Meaning
Semantic technology is set to streamline searches for digital content and take Web services to a whole new dimension. Professor Wolfgang Wahlster from the German Research Center for Artificial Intelligence (DFKI) has been working on man-machine communication for over 30 years. In this interview with SAP.info, he describes how semantic technologies can be used and what role users will play in developing the “Semantic Web”.
What is semantic technology?
Wahlster: In essence, semantics is the science of content and meaning. In IT terms, that means enabling computers to understand the meaning of human language. At the moment, software systems and the Internet are still syntax based. In other words, they focus on the linkage of characters into character strings. When linking from one document to another, computers take no account of meaning. Semantic technologies, on the other hand, allow us to assign content to these links. However, in doing so, it is essential to factor in the ambiguous nature of human language.
How can semantic technologies understand human language?
Wahlster: Semantic technology interconnects terms, like a kind of giant encyclopedia. This is based on the premise that all types of relationships can be defined between terms. For example, terms can be synonyms or antonyms, there are generic terms and subordinate terms, something can exemplify or represent a term. This system of terms and relations creates a semantic network that the computer can use to draw certain conclusions and fill in blanks, so to speak.
What sort of opportunities does this capability offer?
Wahlster: This capability is vital for the interoperability of software systems that work with different terminology sets. By means of a content description that computers can understand, it enables computers to establish whether two terms refer to the same thing. Usually, if a number of departments within a company develop their own specific terminology, computers are unable to cope because the various terms differ in their syntax. Semantic descriptions enable software to pick out terms with the same meaning.
Computers can then also identify when a description is a special case of another. For example, if a call center takes a customer complaint about a software error, a semantic software system would be able to automatically identify that the call is a special variant of an earlier, more general query. This cuts the workload involved in processing the complaint.