White paper
Semantic search
Whereas Web 2.0 upended habits by making the Internet more interactive and allowing users speak out, Web 3.0, the Semantic Web, seeks to provide the web with the intelligence it lacks today.
Memory problems
The Internet has now reached gargantuan proportions. It contains over 12 billion documents, 2 billion images, and hundreds of millions of audio and video files. Every site has its own logic, links and terminology. Given this context, even the easiest search can be a source of confusion and become utterly frustrating. People think in terms of documents where data makes sense within a given context whereas computers "think" in terms of data, which is essentially digital. The result is that no one understands each other. And the Internet's memory remains largely inaccessible.
Information versus knowledge
Nowadays, most of the content available on the web is designed to be read by humans not machines. Although the latter are able to analyse formatted web pages and carry out routine processing, they are currently not able to process semantics. Most search engines don’t understand anything about the requests they receive and they don't understand the results they return. Typing a few phrases into a search engine like Google makes it apparent that engines do not work with semantics. They work primarily thanks to statistical tools. Boolean keyword searches return endless pages filed using quantitative criteria. It's impossible to do approximate or phonetic searches. There are no searches on nominal groups and no suggestions for similar keywords. The result is that everything takes time. Studies have shown that an executive can spend up to eight hours a week searching for documents.
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loginIlse Van den Haute
Edwin Nicasi
Thierry Van Winghe
Fernand Weber
Aurélie Tinel
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