关键词: 病名识别, 词典驱动识别, 手写字符串识别, 集束搜索

Abstract: This paper studies an effective lexicon driven recognition method for on-line handwritten Japanese disease name recognition.The lexicon contains 21，713 disease name phrases，which are stored in a Trie structure.In segmentation，an online handwritten disease name string inputted is over-segmented into primitive segments according to the features such as spatial information between adjacent strokes.Then one or more consecutive primitive segments form a candidate character pattern.The combination of all candidate patterns is represented by a segmentation candidate lattice，where each node denotes a segmentation point and each arc denotes a candidate character pattern.In recognition，this paper uses the beam search strategy to find an optimal segmentation and recognition result，with restricting the candidate character class of each candidate character pattern by the disease lexicon structured into Trie.The algorithm is tested on 500 actual handwritten disease name samples，the average time for processing a disease name is 0.87 second and the recognition rate is 83.16%.

Key words: disease name recognition, lexicon driven recognition, handwritten character string recognition, beam search