Improvement of Efficiency for Interactive Document Retrieval using Transductive Inference

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In the past, traditional interactive document retrieval system retrieved the remained documents by using only the documents that the user evaluated, and had not used information in the remained documents positively. However, the methods using these documents, which are not evaluated by a user, in recent years is proposed in the machine learning research field. The retrieval efficiency can be expected to be improved rapidly by using these methods based on the not evaluated documents. In addition, the interactive document retrieval system should be designed with considering the recognition load of human being In this research, the research purpose is to research and develop the interactive document retrieval method based on the transductive inference using the artificial intelligence methods, especially the machine learning methods.In such a purpose, the concept of the transductive inference was introduced into the frame of active learning with the support vector machine in this research. We proposed a novel document selection method which can display the documents, which are near the user's desire and the system's desire. And we developed this method on a computer and evaluated this method using large bench mark datasets.By the achievement of this research, the user input the keywords to retrieve documents onetime. After this input, the user evaluates the displayed documents and the user can see the relevant documents. Therefore, the user escapes from making keywords to retrieve the documents.