Problem: Today, we use numerous applications to store our work, share pictures, collaborate on a document, and more. Most of them work with the internet, and without a connection, you cannot claim the “ownership” of your data. While this is primarily a big problem for collaborative software tools like Google Docs, a similar situation can be found with social media platforms as well. Without a connection, you cannot see your posts, create a new post, or edit your post.
Annotated data is essential for developing automated solutions involving natural language processing. Linguists have joined the efforts in annotating data. Given the increasing size of data that drives recent innovations, tools that support effective annotation is important. Again, due to the size of the data being annotated, it is most likely that multiple annotators work on this task (either simultaneously or at other times). This project will extend an existing tool by providing collaborative features and validation support. Also, UI/UX improvements are desired.
In recent years, decentralized solutions that respect user content have gained significance. Towards this end, various standards and approaches are being specified and utilized.
The increasing demand for edge computing and the rise of cloud systems have led to the need for efficient resource management and workload distribution
Text readability refers to the problem of measuring the difficulty level in reading a text. In other words, we are interested in how easily a written text can be understood by readers. Text readability score can be used in several application areas including preparing text materials for different educational levels. In this project, you will design and implement a text readability system for Turkish text. You will make use of linguistic properties of texts and use deep learning-based approaches.
Some of the related papers in this task are listed below: