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answers:

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Hi all,

I’m reading towards M.Sc. in Computer Science and just completed first year of the source. (This is a two year course). Soon I have to submit a proposal for the M.Sc. Project. I have selected following topic.

“Suitability of machine learning for document ranking in information retrieval system”. Researchers have been using various machine learning algorithms for ranking documents. So as the first phase of the project I will be doing a complete literature survey and finding out advantages/disadvantages of current approaches. In the second phase of the project I will be proposing a new (modified) algorithm in order to overcome the limitations of current approaches.

Actually my question is whether this type of project is suitable as a M.Sc. project? Moreover if somebody has some interesting idea in information retrieval filed, is it possible to share those ideas with me.

Thanks

+1  A: 

Everything you said is good and should be done, but you forgot the most important part:

Prove that your algorithm is better and/or faster than other algorithms, with good experiments and maybe some statistics (p-value, confidence interval).

If you do that and convince people that your algorithm is useful you surely will not fail :)

George B.
+3  A: 

Ranking is always the hardest part of any of Information Retrieval systems. I think it is a very good topic but you have to take care to -- as soon as possible -- to define a scope of the work. Probably you will not be able to develop a new IR engine but rather build a prototype based on, e.g., apache lucene.

Currently there is a lot of dataset including stackoverflow data dump, which provide you all information you need to define a rich feature vector (number of points, time, you can mine topics of previous question etc., popularity of a tag) for you machine learning ranking algorithm. In this part of the work you could, e.g., classify types of features (e.g., user specific, semantic feature - software name in the title) and perform series of experiments to learn which features are most important and which are not for a given dataset.

The second direction of such a project can be how to perform learning efficiently. The reason behind is the quantity of data within web or community forums and changes in the forum (this would be important if you take a community specific features), e.g., changes in technologies, new software release, etc.

There are many other topics related to search and machine learning. The best idea is to search on scholar.google.com for the recent survey papers on ranking, machine learning, and search to learn what is the state-of-the-art. The very next step would be to talk with your MSc supervisor.

Good luck!

Skarab