An efficient retrieval algorithm for case structures using TRIE

Hierarchical classification is very comprehensive for human and a useful representation for many applications, such as selection of word translation of machine translation systems, semantic representation of natural language analysis, and so on. Especially, for the case structures, the case slot is generally restricted by hierarchical concepts. Case structures are a typical semantic representation for natural language understanding and it has semantic constraints, or roles, for noun phrases in the slot for a verb. Generally, semantic constraints are confirmed by hierarchical relationships between concepts of nouns and the input concepts. With growing hierarchical structures, the number of concepts increases and the length of numerical codes representing concepts becomes long. The frequency of determinations is very high for complex sentences. Multiple concepts correspond to one word. From these reasons, it costs a lot to determine whether a concept for a given word is a sub-concept for concepts of the case slot or not. This paper presents a fast method for determining the hierarchical relationships by introducing trie structures instead of a sequential storage of concept codes. The worst-case time complexity of the determination process by the presented method remarkably improves the one of the sequential storage, which depends on the number of concepts in the slot. The trie structures can be compressed by merging common transitions into one trie. From the simulation results, it is shown that the presented algorithm is 6 to 25 times faster than the sequential storage while keeping a smaller size of tries