Knowledge and Data Processing in a Process of Website Quality Evaluation

Abstract

Different data are present in every branch of computer science, statistics, mathematics, and such, often treated as soft techniques, as human-computer interaction, usability evaluation and ergonomics. Using standard quality evaluation methods the received results obtained empirically or analytically, are not systemized and that increases the cost of output production. Website quality tests are usually characterized by a repeatability of operations, similar to the tasks defined for the offline tests with the participants. Because every person, an object of valuation, is different and his or her answers, actions and behavior during user experience tests are hard to predict. The role of analytic is to select and classify properly transcribed answers of such users and input them to a knowledge database system. We believe that it is possible to standardize and translate all data given as input and received as output during such tests into one consistent model.

Some of artificial computational intelligence methods may help and be effective to increase productiveness of processing the knowledge in a right way basing on the previously received data, by making i.e. feedback to next website analysis. In that case we propose to look closer at uncertainty management, frames and finally propose the idea of expert system enhanced by data mining and inferencing mechanism which will make possible to decide about website quality.

In this paper we generally describe quality of website interface, chosen methods of website usability evaluation, the data obtained during evaluation process and prototypes for organizing data in frames for further use in an expert system.