The mispelling of de-da is a hot topic among Turkish speakers. Not only are there a lot of spelling mistakes for this case, it is can be quite triggering for many people. Unfortunately, spellchecker/correctors are not very successful in detecting these errors.
Edge systems can be thought of as micro-cloud infrastructures that serve devices in proximity. Devices with insufficient computational capacities (AR/VR glasses, mobile gadgets, smartphones depending on the application) can augment their compute power using these edge servers.
Keyword extraction is the process of automatically identifying the important words or phrases in a given text. In this project, you will design and implement a keyword extraction system using deep learning models. You will start by replicating the system described in the paper “Deep Keyphrase Generation” using a recurrent neural network model. Then you will continue with alternative deep learning models. Finally, the pros and cons of these architectures will be compared.
A Web Application for Annotating Dependency Parse Treebanks BoAT (Bogazici University Annotation Tool) [1] is an open-source annotation desktop tool designed for manual annotation of sentences in dependency parse format. It has been developed in the scope of a TÜBİTAK project and was implemented in Python 3. It is used by annotators in several projects to annotate the Turkish treebanks in the UD (Universal Dependencies) framework [2].
The first step in nearly all natural language processing (NLP) applications is applying preprocessing operations to the text. Preprocessing operations include tokenization (segmenting the text into tokens), sentence splitting (dividing the text into sentences), normalization (converting the text into a canonical form), and the like. In this project, you will develop and implement algorithms for preprocessing of Turkish text using deep learning approaches. First, a literature review will be conducted and similar systems for English will be analyzed (e.g. UDPipe, Stanza).
Mobile application stores allow users to provide their feedback on the applications as star ratings and natural language text. The user feedback include useful information on the application as bug reports, feature requests, rationale for praise, or comments on the business logic of the application. The vast number of reviews makes it difficult to process the reviews manually. Machine learning approaches can support product owners to categorize the reviews and extract useful information.
OpenDRIVE is an open format specification to describe a road network's logic. Its objective is to standardize the logical road description to facilitate the data exchange between different driving simulators. In this project, you will generate a map of Bogazici University and surrounding areas in the OpenDrive format.
