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Improvement of Trademark Retrieval Using Pseudo Relevance Feedback

As the number of registered trademarks become larger, the demand for trademark retrieval systems with high accuracy has grown to reduce the burden of human searchers. In particular, precision at high recall is important to avoid erroneous registration of newly submitted trademarks. In this paper we propose a method to realize this by using pseudo relevance feedback, which is a method to search again by using an expanded query formed based on top ranked results of the first search. From the experimental results with the database of about 620, 000 trademarks, we have achieved the improvement of precision by 2.4% at 100% recall as compared to the method without the feedback.