Using data mining techniques in web-based qualifying evaluation and questionnaire poll system

The relevance of the thesis. Currently, the majority of development of information systems is performed with the use of some data mining, machine learning techniques and real-time analytics. These techniques provide to customers new intelligent abilities and features such as quick analysis and smart expectations. Ones of useful systems where data mining abilities can be used are questionnaire poll and qualifying evaluation systems (later survey system). A literature review of research in this field has shown that the existing data mining techniques do not fully reflect the relationship between structure of questionnaire list and appropriate data mining algorithm or technique. The purpose and tasks of the thesis. The main purpose of this work is to research of using data mining techniques in web-based qualifying evaluation and questionnaire poll systems on the example of the module for data mining analysis of open source ―LimeSurvey‖ project.