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Implementation of dictionary is a topic on which research is going on since a long time in the search of a better and efficient algorithm both in terms of space and time complexity. Its necessity has increased due to the advent of recent technical advances in the fields of Pattern Recognition, Image Processing, Natural Language Processing and Machine Learning. The matter is of utter importance when it comes to handheld devices where limited memory availability is a crucial factor. From a programmer’s point of view, the earlier and the conventional methods used to implement a dictionary were hashing and suffix trees which subsequently failed in order to provide the desired space efficiency. By far the data structure which has proved to be the best for storing a dictionary has been Directed Acyclic Word Graph (DAWG), which merges the common suffixes in addition to the common prefixes of the words. The current method used for implementing it, requires construction of an intermediate Trie which puts a lot of memory constraints and is very time inefficient. In this paper, we describe a new method for creating a compressed dictionary with DAWG using Associative Arrays and concepts of Finite Automata on-the-fly as and when a new word is encountered in the lexicographic order. The method presented in the paper doesn’t require construction of an intermediate Trie and hence has a better time complexity. The concept of right language has been crucial to derive the algorithm and is mentioned in the paper. The algorithm is well explained with an example. In the end, the time complexity of the algorithm is analyzed and a small comparison is made in the terms of the maximum memory requirement, for different number of words, for both of the above mentioned methods of constructing DAWG at runtime.

Efficient Construction of Dictionary using Directed Acyclic Word Graph