Named Entity Recognition Based On The Subject Of Intelligent Answering Model

With the development of technology to improve people's quality,Smart Educational aids increasingly broad attention of parents and students,Answering System for the teaching of intelligent knowledge put forward higher requirements for. Specific areas of intelligent question answering system for Chinese named entity recognition has been a difficult and key, at present the actual results of various solutions is also difficult to meet the practical needs of people. With this massive intelligence sub-system for students to use the word natural language questions submitted by the word, Proposed role-based labeling and rules of combining named entity recognition method. Of a high school history for the subject of intelligent question answering model, hereinafter referred to as Intelligent Answering Model.Intelligent Answering Model is built on the basis of a history of disciplinary subject of question answering system,students can access the system via a computer to complete learning activities in Q & A. In order to make intelligent question answering system can correctly understand the problem, and accurate and fast return of the answer,system of sub-word the language of queries processed in named entity recognition, through role-based labeling and rules of the named entity recognition means to enhance the precision rate and recall rate; Answer search strategy uses two kinds of programs:Under normal circumstances the system database to search for answers to find the answer, If the answer does not exist, then search documentation set, set of documents have been pre-treated by the text of library. Furthermore,and answers to improve the strategy will also benefit the library system's proper rate of increase, students satisfied with the results of the query can submit questions storage,look to the right of teachers are not satisfied with the results available to return the issue to re-answer, the answer is the answer to update the library. Answer is stored in a database FAQ, in order to improve retrieval speed and accuracy, we extracted for the questions with common problems in the keywords, combination of key phrases, through the query named entity recognition and other operations carried out to obtain key phrases and key words with the library group phase mapping, and then complete the query- Q & A process.