Intag White papers
Maps of the Human Knowledge and I-Databases
Matchmaking Methodology Global Overview Intag, Miami, USA, July 2002

Juan Chamero: CEO and Project Director
Marcelo Behar: Chief Analyst and Programmer
Daniel Chamero: Chief of Intelligence Synthesis
Nicolás Chamero: Chief Web Developing
Agustin Chamero: Searching Expert

We depict in the figure in black the Web space, the "noosphere" or sphere of knowledge hosting billions of Websites, like bodies in a dark sky, in green the general users querying the Web space, represented by the yellow cone, in gray the most relevant Websites that potentially satisfy the query and the light gray crown the map where there gray region is evolutionary mapped.

General public Internet users have to face today two haunting problems: the inefficiency of search engines and the matchmaking inefficiency of most of the commercial business Websites. Without any doubt what they want, what they need, is "up there" but they could get it far from easy, entering into despair and quitting, restricting themselves to make only use of email and some limited forms of entertainment. INTAG- Intelligent Agents Internet Corp, a Research and Development firm of Miami, has created a Match Making Methodology to solve these two problems, closely related to Information Retrieval and Artificial Intelligence.

Two types of problems could then be solved: a) retrieving what users need, at large a matchmaking process between information and knowledge offered by Website owners hosted in the Web space and information demanded by users, throughout intelligent maps, and; b) matchmaking optimization between owners that want to sell something and users that want to acquire what they need, throughout intelligent databases. In both cases, the methodology allows the buildup of a type of Expert Systems named FIRST, which stands for "Full Information Retrieval System Thesaurus", that behave as the facilitators between owners and users. In both cases, the Expert Systems behave evolutionary trying to match offer versus demand continuously and tending to the utopia of trying to satisfy demand fully and in one query, which means in one click.


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