Recognizing Permuted Words with Vector Symbolic Architectures: A Cambridge Test for Machines.

This paper proposes a simple encoding scheme for words using principles of Vector Symbolic Architectures. The proposed encoding allows finding a valid word in the dictionary for a given permuted word (represented using the proposed approach) using only a single operation– calculation of Hamming distance to the distributed representations of valid words in the dictionary. The proposed encoding scheme can be used as an additional processing mechanism for models of word embedding, which also form vectors to represent the meanings of words, in order to match the distorted words in the text to the valid words in the dictionary. [ABSTRACT FROM AUTHOR]