Abstract

Information society: we call often so our society. It means we are collecting day by day lot of data. On the other"br" hand we need lot of information. How can we transform data into information? One way is the data mining and"br" data processing. In this paper we show our previous and latest results and their comparison in the field of public"br" transport. We introduce a method to discover information among the data of public transport usage (boarding"br" and alighting). We describe how it is possible to find the connection between planning zones and raw data of"br" boarding and alighting. The method shown in this paper is the example that the data of a possible e-ticketing"br" system inherits much more information than we can image."br" The paper shows previous calculation results in a city with 130 thousand inhabitants, the new result in a city with"br" 40 thousand inhabitants and the comparison and conclusions of the results of these two different cities.