Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Enformatik Enstitüsü, Bilişim Sistemleri Anabilim Dalı, Türkiye
Tezin Onay Tarihi: 2018
Öğrenci: GÜLİZ BULUT
Danışman: TUĞBA TAŞKAYA TEMİZEL
Özet: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, data set consisting of type 2 diabetes related web pages is utilized. “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 KB on type 2 diabetes treatment and enables to produce a trustworthy input for evaluation. In light of this KB, the data set 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.