Similarity Between Semantic Spaces

One of thechallenges in Latent Semantic Analysis (LSA) is deciding which corpus is best for a speci c ̄ applica-tion.Imp ortant factors of LSA in°uence the generation of high quality LSA space including the size of the cor-pus, the weight (local or global) functions, number of dimensions to keep, etc. These factors are often di±cult to determine and as a result hard to control for. In this paper, we provide a general method to measure simi-larity between semantic spaces. Using this method, one can evaluate semantic spaces (such as LSA spaces) that are generated from di®erent sets of parameters or di®er-ent corpora. The method we have develop ed is generi