I use Libsvm to train data and predict classification on semantic analysis problem. But it has a performance issue on large-scale data, because semantic analysis concerns n-dimension problem.
Last year, Liblinear was release, and it can solve performance bottleneck. But it cost too much memory. Is MapReduce the only way to solve semantic analysis problem on big data? Or are there any other methods that can improve memory bottleneck on Liblinear?