二阶对角递归神经网络的算法研究及应用的中期报告【摘要】本文研究了二阶对角递归神经网络的算法，分析了其优点和局限性，并探讨了其在自然语言处理中的应用。首先介绍了二阶对角递归神经网络的基本结构和训练方法，然后通过实验比较了其和其他几种神经网络模型在词性标注和命名实体识别任务中的表现。实验结果表明，二阶对角递归神经网络在一些自然语言处理任务中能够取得非常优秀的性能，并且相对于其他几种神经网络模型具有一定的优势。最后讨论了二阶对角递归神经网络的一些发展方向和未来研究的方向。【关键词】二阶对角递归神经网络，自然语言处理，词性标注，命名实体识别【Abstract】Thispaperstudiesthealgorithmofthesecond-orderdiagonalrecursiveneuralnetwork,analyzesitsadvantagesandlimitations,anddiscussesitsapplicationsinnaturallanguageprocessing.First,thebasicstructureandtrainingmethodofthesecond-orderdiagonalrecursiveneuralnetworkareintroduced.Then,itsperformanceinpart-of-speechtaggingandnamedentityrecognitiontasksiscomparedwithotherneuralnetworkmodelsthroughexperiments.Theexperimentalresultsshowthatthesecond-orderdiagonalrecursiveneuralnetworkcanachieveverygoodperformanceinsomenaturallanguageprocessingtasks,andhascertainadvantagescomparedtootherneuralnetworkmodels.Finally,somedevelopmentdirectionsandfutureresearchdirectionsofthesecond-orderdiagonalrecursiveneuralnetworkarediscussed.【Keywords】second-orderdiagonalrecursiveneuralnetwork,naturallanguageprocessing,part-of-speechtagging,namedentityrecognition