We applied active learning techniques based on Support Vector Machine for evaluating documents each iteration, which is called relevance feedback. Our proposed approach has been very useful for document retrieval with relevance feedback experimentally. However, the initial retrieved documents, which are displayed to a user, sometimes don?t include relevant documents. In order to solve this problem, we propose a new feedback method using information of non-relevant documents only. We named this method non-relevance feedback document retrieval. The non-relevance feedback document retrievals are based on One Class Support Vector Machine and Support Vector Data Description. Our experimental results show that One Class Support Vector Machine based method can retrieve relevant documents efficiently using information of non-relevant documents only.