An interactive and iterative learning-based intelligent construction method for a geographical name tagging corpus, the method comprising: generating a word vector matrix of words and a disambiguation matrix of the words in sentences in an initial corpus; after splicing, inputting Bi-LSTM and CRF integration models for training to generate a geographical name recognition model; embedding the geographical name recognition model into a human-computer interactive geographical name tagging platform for human-computer interactive correction; and fusing the initial training corpus with a tagged geographical name corpus to optimize the parameters of the geographical name recognition model until the iterative training and learning ends when the constructed corpus satisfies the requirements, thereby achieving the intelligent construction and optimization of the geographical name corpus. The method may effectively solve the problems of the current lack of geographical name corpus data, slow updating, the time-consuming, laborious and low-efficiency manual construction of a geographical name corpus, etc., and may effectively achieve the intelligent updating of the geographical name tagging corpus for multi-source, dynamic, heterogeneous and exponentially growing Internet text.
INTERACTIVE AND ITERATIVE LEARNING-BASED INTELLIGENT CONSTRUCTION METHOD FOR GEOGRAPHICAL NAME TAGGING CORPUS