Hi,
Sorry to bump this quite old thread, but I have done some research and implementation on this topic and thought it might be beneficial for the community to share some of it.
First of all, I use data from the interim reports of listed firms, collected from various sources (mainly from Europe). The reports are condensed to a high-dimensional vectors, which represent the textual information in the documents. These can be used in multiple ways, for example in clustering (with DBSCAN as you mentioned), which leads to similar companies appearing close to each other. There are also some academic research about companies that change the content of their reporting, leading to lower alpha in future quarters.
I have compiled this information to a website finsim, where the results can be found. I you find this interesting, feel free to give suggestions and feedback, the project is still quite rough around the edges, thanks.
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