The semantic technology, the last mile of information

Structures that are able to explore information and to identify concepts, 
allow to realize intelligent search engines.


Probably, our grandchildren will consider the years 2000 as the “99miles age”, the period in which there was always the last miles left. The period in which the processing power of computers reached the maximum from the available technology, in which the storage ability was boundless, the cost was accessible and the knowledge, understanding as the availability of data and information, reached an unimaginable level of completeness.

At the same time they will try to understand why, with all these data, nobody (or only somebody) was worried about the realization of a structure, which was able to analyze and understand the information.

The metaphor is that of the librarian: I can ask for Paul Auster’s book, but I can’t think to obtain information, only declaring that I am interested in reading some authors, who explored the relationship between identity and language. Different from human librarians, computers can read every text and, in spite of this, they provide the same information.

The semantic technology positions itself in the last miles of information, that of comprehension.  A comprehension that is very useful, for example, for users, in an organization or on the web, who have to take part in a conversation with that librarian, who seems a little silly. 

When Tim Berners Lee exhibited his project at CERN, he had very clear ideas ”The relationship parent-son becomes a limit when the information structural scheme is more complex. Not even the keywords are an accessible way and so we have to do an additional and more drastic step”. 

The semantic technology allows to explore the information and to identify the concepts, instead of the easy words, and it has two fundamental elements: the ability of a machine to read a text in a syntactic way and the possibility to insert key-words in a semantic net. For example, in the sentence “I’m looking for a job as a farmer”, the system understands that the text speaks about the research of an employment and it automatically excludes all the different meanings of “farmer”, understood as “director of a farm”.

Thanks of this technology, is possible:

  • optimizing the documentary research inside of an organization;
  • ​managing in an automatically way the correspondence in a Help Desk;
  • ​analyzing, without human operations, the CV used for recruitment;
  • monitoring the web-competition for the e-commerce systems;
  • last, but not least, is the intelligence search engine for the business and institutional gateways : thinking at this, our grandchildren maybe could laugh a lot.