Efficient method for similar floor plan retrieval in patent examination using deep learning

Abstract

Patent literature consists of three parts: claims, descriptions, and drawings. The examiner must retrieve the database using classification symbols and text to check whether claims include existing documents. This paper aims to treat a patent drawing with variations as structured graphs and to establish an efficient method for similar floor plan retrieval in patent examination. First, we labeled the patent drawings with room types. Second, we stipulated the connection relationships of the rooms based on rules and converted the labeled patent drawings into graphs. Third, by reflecting claims in the graph similarity based on the maximum common subgraph, we implemented a similarity floorplan search that considered the unique circumstances of patent examination. Finally, using an existing reviewed literature, we verified the usefulness of the proposed method in terms of similarity-based patent sorting results and computational speed.