Rough Set Theory for Supporting Decision Making on Relevance in Browsing Multilingual Digital Resources

Abstract

Browsing digital library (DL) collections seems to pose a challenge for a user owning to the number of factors like for instance, operability of the system, interface readability or clarity, and retrieval efficiency directly related to it, or the number of digital items within the user’s domain. However, when it comes to searching for an item in a foreign language to the user, the number of the factors arises even more which translates proportionally to the growing number of clicks aimed to retrieve the target item. Such a procedure usually leads to disheartening the user from browsing the digital collections. Our study into the user’s behavior interacting with multilingual DL system is set out to propose a rough set theory based model which automatically generates a decision rule based on the minimum number of the decision factors. Analyzed is a set of the predefined factors specifically influencing the user’s decision on clicking an item of his special interest. We aim to limit the number of the factors however, without losing the precision of the final user’s decision. To our best knowledge, rough set theory has not been implemented for multilingual decision making purposes.