In this blog post, I will talk about how to find a good thesis topic on machine learning. This is an important question for many students that are required to select a topic for their research and want to work on machine learning. Choosing a good research topic is a critical step in the research process to ensure the success of the research and for publishing good papers.
What is a good research topic?
A good research topic is a research problem that is:
(2) challenging to solve (cannot just be solved by applying existing techniques) but not too challenging or long,
(3) useful (otherwise, there is no reason to do the research), and
(4) a problem that is interesting for other researchers or has applications.
It should also be clear that a research topic is not equal to doing a programming or software development project. Just solving a software development problem is generally not research. Research is about solving a novel and difficult problem that requires to develop some inovative solution.
How to find a good research topic on machine learning?
To find a good research topic, it is important to know what other researchers have done in recent years. Thus, to select a topic, one should first read papers in good journals and conferences to see what other researchers have been doing. By reading recent papers, one can try to think about the limitations of these studies and what could be improved, or what other researchers have not done yet (because there is no point to do the same thing again). Reading the literature requires some time and is not so easy to do but is very important to choose a good topic. For the young students, it is recommended to ask advices from their supervisor during this step. The supervisor should be able to suggest some good papers to read as starting point and to validate the research topic ideas. When reading paper, one can pay attention to the related work section and conclusion, which sometimes highlight some limitations of previous studies and can give some ideas for research.
Generally, it is a good to work on some research area that other researchers are interested in rather than working on some obscure problems that have few applications.
After finding some idea that is novel, it is also important to keep searching for papers to make sure that the idea is really novel and no one has done it before. If someone did it already, it is better to find this issue as early as possible to avoid wasting time on pursuing a research idea that has been done before. When searching for other papers, it is also important to find the right keywords for searching. Some research topic may have already been studied but with a different name. Thus, when searching for papers, it is important to try various keywords and to keep searching to make sure that the literature has been checked carefully.
How to describe your research topic?
A common misconception about choosing a research topic is to think that just choosing a title is good enough for choosing a research topic. But it is not. A research topic should be defined clearly and with more details.
For example, a topic title like ‘machine learning for image processing’ is too broad and does not mean much about what one would like to do. What kind of machine learning technique? What kind of image processing task? And what is the originality? All of this could be explained more clearly with a more detailed description.
To clearly define your research topic, I recommend to write some text explaining:
– the title,
– why the problem is important?
– what are the limitations of previous studies that this research will address?
– why that research problem is challenging?
– and give a sketch of some possibilities for solving the problem.
If you can answer the above questions, then it means that you have carefully thought about your research topic.
You may also ask some senior researchers to look at your research topic to confirm that it is a good topic.
In this blog post, I have discussed the problem of searching for a research topic in machine learning. Hope this has been helpful. If you have some comments, please leave them in the comment section below.
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.