Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253

Browse

Filters

2005 - 20072

Settings

Publisher: search.filters.publisher.World Acad Sci, Eng & Tech-waset

Search Results

Now showing 1 - 2 of 2
  • Conference Object
    Citation - WoS: 1
    Information/Knowledge Society and Europe
    (World Acad Sci, Eng & Tech-waset, 2005) Aktaş, Ahmet Ziya; Aktas, A. Ziya; Bilgisayar Mühendisliği
    During the last decade some long lasting changes and developments are shaping the global society. The world is entering a new society which is already named as information or knowledge society. In the paper, information/knowledge society is elaborated first. Starting in the year 2000, European Union has initiated some special projects such as eEurope and eEurope+ and activities such as Bologna Process and Socrates/Erasmus Program. The paper will review these activites in relation with information or knowledge society. Before paper ends with a conclusion, some views relevant to the topic are also presented.
  • Conference Object
    Citation - WoS: 1
    Modeling the Symptom-Disease Relationship by Using Rough Set Theory and Formal Concept Analysis
    (World Acad Sci, Eng & Tech-waset, 2007) Bal, Mert; Sever, Hayri; Sever, Hayri; Kalipsiz, Oya; Bilgisayar Mühendisliği
    Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.