Create and contribute in NLP/ML components from the OpenReq project
The main goal of OpenReq is to build an intelligent recommendation and decision system for community-driven requirements engineering. One of the main technologies used for this purpose is Natural Language Processing, which offers a large set of features to evaluate and extract information from these requirements.
At HackNLP, you will learn the basics of the main components developed at OpenReq that focus on applying NLP techniques to the requirements engineering field. And you will be challenged to build an innovative, accurate solution giving a contribution by your own!
How good are the results with the respect to the challenge the project tries to solve? Are they better/equal/worse than the ones provided? Are there any remarkable improvements?
Is it an efficient solution? Does it only work at a small PoC or could it be extend to a bigger, general, realistic UC? Has this dimension been considered while building the solution?
Does the project contributes in some way on the filed the challenge is based on? Which are the main features of the proposal? Do they provide an improvement on the solution?