LRS Seimo narių grupavimas pagal balsavimą ir balsavimo kitimo aptikimas ; Lithuanian Parliament members grouping by their voting behavior and it's change detection
Politicians declare their behavior in different ways, so the only way to control it - monitoring. In this thesis tools for Lithuanian Parliament Members voting behavior are analyzed. The question is following: can Information technologies tool help to determine how membership in a faction or the position (opposition) is related with voting behavior? The main objectives of this work are Lithuanian Parliament members grouping by their voting behavior and its' change detection. In the thesis the 2008-2012 of the Parliament activities are analysed using statistical voting analysis. We use clustering for grouping members of the Parliament. A loose definition of clustering could be the process of organizing objects into groups whose members are similar in some way. A cluster (group) is a collection of objects which are similar between them and are dissimilar to the objects belonging to other clusters. We overviewed different clustering methods and their principles of operation, described the distance between the objects of calculation methods, quality evaluation criteria in this work. Voting data is stored in MySQL database, hence a tool was created for data processing. We describe all the stages of the work: the use of tools, coding of the votes, division of the votes into the periods. The following techniques were chosen: K-Means, Hierarchical Clustering with Complete (furthest neighbor), Average, Single (nearest neighbor) linkage. We use Euclidean and Manhattan methods for dissimilarity (distance) calculation. For the quality evaluation of clustering Purity, RAND and NMI are used. The data of the voting are divided into different periods (all sessions, months). For the grouping of members of the Parliament WEKA tool is used, for detection of voting changes RapidMiner tool is applied. This work concludes with experimental results, conclusions and the plans of future research.