The Partition Heuristic Information Extraction Algorithm of Unstructured Data

In this paper, we propose a method that extracts attributes of given entity from unstructured data for the field of logistics by using the idea of divide and conquer as to the characters of logistics information. After the full study of logistics information, we make a statistical analysis for the text logistics information and summarize the common attributes of text information entity. According to the different attributes and attribute values, we divided text information entity by the idea of divide and conquer. As to the entity we get from last step we make an internal processing based on segmentation method of tagging and graph. We extracted valuable attributes and attribute values from the unstructured data. Experimental results show that this method is valid for the logistics information which we achieve from a well-known logistics system.