@article{Nagy_Mihalydeak_Aszalos_2019, title={Different Types of Search Algorithms for Rough Sets}, volume={24}, url={http://cyber.bibl.u-szeged.hu/index.php/actcybern/article/view/3999}, DOI={10.14232/actacyb.24.1.2019.8}, abstractNote={<p><span class="fontstyle0">Based on the available information in many cases it can happen that two objects cannot be distinguished. If a set of data is given and in this set<br>two objects have the same attribute values, then these two objects are called indiscernible. This indiscernibility has an effect on the membership relation,<br>because in some cases it makes our judgment uncertain about a given object. The uncertainty appears because if something about an object is needed to be<br>stated, then all the objects that are indiscernible from the given object must be taken into consideration. The indiscernibility relation is an equivalence<br>relation which represents background knowledge embedded in an information system. In a Pawlakian system this relation is used in set approximation.<br>Correlation clustering is a clustering technique which generates a partition. In the authorsâ€™ previous research the possible usage of the correlation clustering<br>in rough set theory was investigated. In this paper the authors show how different types of search algorithms affect the set approximation.</span></p>}, number={1}, journal={Acta Cybernetica}, author={Nagy, David and Mihalydeak, Tamas and Aszalos, Laszlo}, year={2019}, month={May}, pages={105-120} }