Research On Question-Answering Technology In The Field Of Economic Responsibility Audit

Economic responsibility audit is an audit of the relevant economic activities of the leading cadres of the party and government and the leaders of the state-controlled enterprises during their tenure of office.Auditing economic responsibility plays an important role in the governance of corruption.As the round of trial and simultaneous audit are gradually carried out,the auditors have an increasingly strong demand for knowledge acquisition related to economic responsibility audit.However,knowledge related to economic responsibility audit is fragmented.Searching related knowledge through search engine requires manual examination and screening of knowledge and is difficult to obtain.Under such circumstances,this paper builds a domain question answering system in the field of economic responsibility audit,which can help the people to obtain relevant knowledge and reduce corruption.This paper completed domain knowledge base construction and answer retrieval.In the knowledge base building part of the use of web crawler technology from the Internet encyclopedia,related agencies and Knowledge quiz website access to knowledge,and by improving the algorithm of domain word decision based on logistic regression to ensure the rationality of the crawling results,the final construction of domain thesaurus and FAQ library was completed.In the part of answer retrieval,multidimensional question error correction and convolution neural network neural network based answer retrieval are designed.Among them,error correction is made by using Bayesian method and N-Gram language model to correct the question from spelling and word order dimension.The calculation method of edit distance is optimized from the point of phonetic syllables.Based on convolution neural network,the answer retrieval algorithm designs the neural network structure including input layer,convolution layer and pooling layer,In the process of feature extraction,this paper proposes a new vocabulary weighting technique to enrich the model features.In the end,the accuracy and validity of the algorithms and models used in this paper was verified through comparative experiments and can provide the question answer ability in the field of economic responsibility audit.