- Çağıl Sönmez, Arzucan Özgür, and Erdem Yörük. 2016. Towards building a political protest database to explain changes in the welfare state. In Proceedings of the 10th ACL Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH 2016), pages 106--110, Berlin, Germany, August, 2016. Association for Computational Linguistics. bibtex pdf
- Çağıl Sönmez and Arzucan Özgür. A Graph-based Approach for Contextual Text Normalization. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 313-324, Doha, Qatar, October, 2014. Association for Computational Linguistics. bibtex pdf slides
- Çağıl Sönmez. "Text Normalization Using Lexical and Contextual Features" M.Sc. Thesis. Bogazici University, 2014
During my MS, I studied two different topics: Semantic Analysis and Text Normalization. I wrote my MS thesis on Text Normalization of Informal Text. I aimed to understand the dynamics of non-standard (Out of Vocabulary - OOV) words using contextual information within the phrase. Our model was a based on a word association graph where the contextual relations between words are translated into directed edges of several degrees, as well as the lexical features. Our paper "A Graph-based Approach for Contextual Text Normalization" was published in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP 2014).
In the first year of my PhD studies, I took part in a Tübitak Funded project where we developed a Question Answering System called Hazircevap for the use of Turkish high school students. My main focus on this project was on Cross Lingual Information Retrieval (CLIR). I extended Hazircevap system such that it was able to find answers in resources in English and to translate them back to Turkish.
Currently I am working as a part of a team of three with Erdem Yoruk and Deniz Yuret from Koc University on a research project: "Information extraction about social movements of the last decade in Brazil using newswire text as a part of a historical comparative sociological research project on the relationship between social welfare systems and movements in Brazil, Turkey and Korea". This project is funded by the European Commission’s Marie Curie Program. Our main goal is to extract event information from newswire text using Machine Learning techniques.