Hi Rupert! Nice to see great feedback on this topic!. I wanted to comment part of your previous email:
En 24 de octubre de 2014 en 12:31:39, Rupert Westenthaler (rupert.westentha...@gmail.com) escrito: I fear that each disambiguation approach will come with its own data model. Mainly because the way data is kept is central for performance. Also based on what I have seen up to now keeping everything in-memory is the way to go. For Aida-Light I suggest to keep the current solutions. The requirement of about 50GByte RAM for Yago is anyways quite OK. If we can add support for more focused datasets one will often end up with far less entities. This is also a way to keep resource requirements down. I completely understand your point but I partially disagree. I find the memory consumption requirement quite tough. It may prevent a lot of people to give it try or experiment with it. Actually, Chalitha had serious problems to find a machine for testing it. I agree that probably it is difficult to find a valid architecture for any disambiguation approach, but focusing only in Aida-Light I think that it is worth to provide also an other data management solution. It will affect the performance for sure, but at least it will let people use it without a super machine. I’m actually thinking in alternatives that can “simulate” memory access using the disk like LevelDB or similar. Makes sense? Cheers, Rafa
