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Yayın Decision making and Yarsoy decision support tool(Işık Üniversitesi, 2002-09) Atasoy, Ercan; Yarman, Bekir Sıddık Binboğa; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Elektronik Mühendisliği Yüksek Lisans ProgramıEvery human makes decisions in the course of his interactions with the world and other human acting in the world. To make good decisions, we need knowledge about events that occur in the world and preferences we have. Decision Support Systems try to gather information, keep it in database, classify it, give a fast and easy access to his information and by analyzing it help user to make consistent decisions. In this thesis a model driven decision support tool with the name 2YARSOY3 is developed using designated decision making models. It is developed using C++ Builder 5.0 programming tools. YARSOY is very flexible, user friendly and unique with its models. It can be used for a daily life decisions such as car or job choices, employee selection, vote selection and swot analyses. People usually make decisions by taking three or five factors into account. In order to attain the existent objectives, the events, factors and alternatives that will realize the objective must be analysed cearfully. This program gives us opportunity to evaluate, compare and analyse the events and alternatives in detail based on mathematical methods.Yayın Big data storage and automated text summarization in Turkish text(Işık Üniversitesi, 2018-06-19) Aysu, Erdinç; Yıldız, Olcay Taner; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans ProgramıThe subject of this study is storing the large datasets in accordance with Big Data ecosystem and to extract the summary sentences of a text in Turkish, apply the automatic text summarization process which is a subtopic of Natural language processing (NLP). For this purpose, Turkish news articles were collected and the study was carried out through these texts. For the performance test of the work done, 50 different news textiles were given to 20 different persons and 3 sentences which were considered important from each other were asked to be selected and their results were compared with each other. Then, the results from the people were compared with the results from this study. As a result of the test process, the summation performance of the work was measured approximately as thirty-six percentage.Yayın Driver recognition and driver verification using data mining technigues(Işık Üniversitesi, 2007-09-25) Benli, Kristin Surpuhi; Eskil, Mustafa Taner; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans ProgramıIn this thesis we present our research in driver recognition and driver verification. The goal of this study is to investigate the affect of different classifier fusion techniques on the performance of driver recognition and driver verification. We are using five different driving behavior signals for identifying the driver identities. Driving features were extracted from these signals and Gaussian Mixture Models were used for modeling the driver behavior. Gaussian Mixture Model training was performed using the well-known EM algorithm. In recognition study posterior probabilities of identities called scores were obtained with the given test data. These scores were combined using different fixed and trainable (adaptive) combination methods. In verification study we compared posterior probabilities with fixed threshold values for each classifier. For different thresholds, false-accept rate versus falsereject rate was plotted using the receiver operating characteristics curve. We observed lower error rates when we used trainable combiners. We conclude that combined multi-modal signal or classifier methods are very successful in biometric recognition and verification of a person in a car environment.Yayın Data mining techniques customer relationship management : a case study for Doğuş Otomotiv(Işık Üniversitesi, 2003-10) Gören, Olga Ufuk; Yarman, Bekir Sıddık Binboğa; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Enformasyon Teknolojileri Yüksek Lisans ProgramıCustomer Relationship Managment has recently become a very important investment for many companies. The value of the customer is expressed more clearly with this new concept and it's demonstrated through its applications. The increased importance of focusing on the customer has been recognized in related academic studies in recent years. CRM has great importance in helping companies find the answers to questions such as ''What types of customers exist in which markers?'', ''What do they demand from companies?'', ''Who should be targeted as a customer?''. In fact it is a corporate strategy itself. In order to be successful, a company needs to combine the whole CRM concept with its vision. Furthermore, CRM is a strategy which aims to increase the improtance of every stakeholder of the company. With CRM, it is easy to realize the great value sone data for future of a company even though such data for the future of a company even though such data were not considered important in the past. CRM also provides ways of evaluating these data, and creating new goals out of results. The aim of this thesis is to study the CRM implementation process and show how customer data is being classified, analyzed and assessed, making use of the results of RFM analysis and demographical analysis as implemented in Doğuş Otomotiv. The importance of this thesis is that it keeps customers and their information in a data warehouse, so as to be available for effective use and analysis when needed. This analysis will help companies organize their marketing and sales activisties so as to respond to the right customer, at the rigth time, in the right way, and at the right place within their market.Yayın Differentially private attribute selection for classification(Işık Üniversitesi, 2015-06-18) Var, Esra; İnan, Ali; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans ProgramıAny study on processing or analyzing large data sets that contain personally sensitive data should conform against some form of privacy protection mechanism. Otherwise, malicious people can aceess these data sets to extract private information and use this private information in agency operations, blackmail, fraud or any other harmful actions. Importance and necessity of privacy preserving data mining is increasing day by day, hence public and government lawmakers, privacy advocates and the media are drawing more and more attention to this subject daily. This thesis proposes an approach to that selects features from a data set according to the differential privacy mechanism and implements this proposed solution on a popular data mining library called WEKA.
