Tanszéki konzulens: 

Tamás Mészáros associate professor Szoba: IE437 Tel.: +36 1 463-2899 Email: meszaros (*) mit * bme * hu

Project proposal

During the project work students develop natural language processing (NLP) systems for various real-world tasks like text classification (e.g. sentiment analysis, authorship attribution, topic identification etc.) and automated text annotation (e.g. named entity recognition, part-of-speech tagging etc.). Application areas include business and medical information systems and digital humanities. Cooperating with our industrial and academic partners is a possibility for skillful and motivated students.

Customize the proposal according to your ideas, e.g.:

• information extraction from online sources (Web, Facebook, Twitter etc.)
• annotate text with knowledge (e.g. Link Open Data sources)
• identify hate speech or fake news
• identify unknown authors or classify authors based on stylometry analysis
• ... you name it

Requirements

What do you need to successfully fulfill your task

• good knowledge of programming languages, especially Python
• basic knowledge of natural language processing terms and methods (see for e.g. Chapter 23. and 24. in AIMA)
• very basic understanding of statistical methods like clustering and machine learning tools
• motivation

Results

What to expect to learn during your work

• how NLP tools work in practice
• how to model natural language texts for various purposes and how to build and use these models
• what kinds of text attributes can be examined and used
• how to solve different kinds of NLP-tasks

How to apply

• collect your ideas (what problems you would like to solve, how you would do it etc.)
• assess your experience (programming knowledge, previous NLP-related work etc.)
• write a short introductory letter to the supervisor including the above