Independent semantic feature extraction algorithm based on short text - HU Jia-ni; GUO Jun; DENG Wei-hong; XU Wei-ran (Tongxin xuebao)
An independent semantic feature extraction algorithm was proposed,aiming at reducing the sparseness of short text and enhancing its capability of semantic expression.The algorithm first makes use of latent semantic indexing to re-duce the dimension and wipe off noise,and then it introduces independent component analysis to extract statistic inde-pendent and semantic features.Experimental results prove the feasibility of the algorithm and demonstrate it is superior to latent semantic indexing.