It is an obstacle for the beginner to use keywords to search for related documents from the literatures, especailly for the one who was not familar with the concept of what he was looking for. This reasearch includes two processes, 『the computation of document similarity』 and 『document vectorization』. Regarding 『document vectorization』, we transfer each document into one vector by appropriate pattern weighting according to the distribution of the patterns. 『the computation of document similarity』 means to compute the similarities between the vector of query document and the one of each document in the literature after transfering the query docuemnt into one vector, and to give the order of the documents for user's reference by sorting the values of these similarities. We have two approaches to have the set of the patterns, including『dictionary』 and 『content』, and use cosine similarity to evaluate the similiarity of two vectors. Experimental results showed that the value of precision achieved by the『dictionary』was higher than that achieved by the 『content』.