Natural language processing (NLP) focuses on machine learning techniques applied to natural languages in order to build automated systems that can analyse, understand, and generate natural human languages.

Hacettepe University Natural Language Processing Research Group (HUNLP) is concerned with the natural language processing (nlp) applications and various fields in computational linguistics. We focus on mainly the following areas:

• Morphological segmentation: We are interested in morphological segmentation of agglutinating languages as a learning problem, which involves statistical learning as an unsupervised learning problem.
• Syntax: We are interested in syntax, that involves learning parts-of-speech in a given text as another learning problem in computational linguistics.
• Example Based Machine Translation: We are interested in example-based machine translation systems between English and Turkish. We have developed a system which learns translation templates from bilingual translation examples using machine learning techniques.
• Text Summarisation / Keyphrase extraction: We do research in text summarisation and keyphrase extraction problems. We have developed text summarisation and keyphrase extraction systems which extract summaries and keyphrases of English and Turkish documents.
• Information Extraction: We have developed a Name Entity Recognition system.
• Sentiment Analysis: Sentiment analysis on social media documents.
• Question Answering Systems: We have worked on factoid question answering systems.
• Word sense discovery: Graph based word sense discovery from Collaboratively built Semi-structured Information
• Topic segmentation
• Morphological disambiguation

We would be pleased to have new members in our research group, who are interested in natural language processing. Please feel free to contact us, if you think that your interests match with ours.