Exploiting Latent Semantic Relations in Highly Linked Hypertext for Information Retrieval in Wikis

Current word completion tools rely mostly on statistical or syntactic knowledge. Can using semantic knowledge improve the completion task? We propose a language-independent word completion algorithm which uses latent semantic analysis (LSA) to model the semantic context of the word being typed. We find that a system using this algorithm alone achieves keystroke savings of 56% and a hit rate of 42%. This represents improvements of 6.9% and 17%, respectively, over existing approaches