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This paper presents a syntactic analysis method that first detects conjunctive structures in a sentence by checking parallelism of two series of words and then analyzes the dependency structure of the sentence with the help of the information about the conjunctive structures. Analysis of long sentences is one of the most difficult problems in natural language processing. The main reason for this difficulty is the structural ambiguity that is common for conjunctive structures that appear in long sentences. Human beings can recognize conjunctive structures because of a certain, but sometimes subtle, similarity that exists between conjuncts. Therefore, we have developed an algorithm for calculating a similarity measure between two arbitrary series of words from the left and the right of a conjunction and selecting the two most similar series of words that can reasonably be considered as composing a conjunctive structure. This is realized using a dynamic programming technique. A long sentence can be reduced into a shorter form by recognizing conjunctive structures. Consequently, the total dependency structure of a sentence can be obtained by relatively simple head-dependent rules. A serious problem concerning conjunctive structures, besides the ambiguity of their scopes, is the ellipsis of some of their components. Through our dependency analysis process, we can find the ellipses and recover the omitted components. We report the results of analyzing 150 Japanese sentences to illustrate the effectiveness of this method.