Thesis defense - Güliz Bulut

Graduate School of Informatics /Information Systems

In partial fulfillment of the requirements for the degree of Master of Science Güliz Bulut will defend his thesis.


Date: 3rd September 2018

Time: 10:00 AM

Place: A-212

Thesis Abstract :People frequently access Internet to look up health information. However, as the quality of websites may vary significantly, the treatment recommendations and guidelines provided by some of these web sites may be fallacious. Consequently, patients may unfollow their current treatments suggested by their doctors or start following unfounded treatments. In this thesis, an automated approach is presented to estimate information coverage of websites. The approach is based on a domain-dependent standard knowledge base (KB) and enhanced by open source resources. Elastic net regularized regression is used to construct a model for estimation. As a case study, corpus of type 2 diabetes related web pages is selected. “Standards of Medical Care in Diabetes” published by American Diabetes Association is processed to obtain factual data about treatment of type 2 diabetes. This standard serves as a detailed knowledge base on type 2 diabetes treatment and enables to produce a trustworthy input for evaluation. In light of this KB, the corpus of type 2 diabetes related web pages is processed to retrieve their coverage of factual information. It is observed that, extracting significant terms from a domain-dependent knowledge base provide a basis to measure information coverage of a source