A SOLUTION TO PLATES PROBLEM - THE LATENT SEMANTIC ANALYSIS THEORY OFACQUISITION, INDUCTION, AND REPRESENTATION OF KNOWLEDGE

How do people know as much as they do with as little information as th ey get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new genera l theory of acquired similarity and knowledge representation, latent s emantic analysis (LSA), is presented and used to successfully simulate such learning and several other psycholinguistic phenomena. By induci ng global knowledge indirectly from local co-occurrence data in a larg e body of representative text, LSA acquired knowledge about the full v ocabulary of English at a comparable rate to schoolchildren. LSA uses no prior linguistic or perceptual similarity knowledge; it is based so lely on a general mathematical learning method that achieves powerful inductive effects by extracting the right number of dimensions (e.g., 300) to represent objects and contexts. Relations to other theories, p henomena, and problems are sketched.