基于短语一致性图的文本连贯性评价对精神分裂症症状的识别
Evaluating text coherence based on the graph of the consistency of phrases to identify symptoms of schizophrenia
摘要：
分析了基于文本连贯性估计的精神分裂症症状检测的不同方法。建议在短语层面上对语篇进行分析。提出了基于短语一致性图的语篇语义连贯性和衔接性评价方法。语义连贯性，衔接，和其他语言特征（词汇多样性，词汇密度）已被考虑到形成特征向量的训练模型分类器。分类器的训练已经在英语访谈集上进行。根据检索结果，分析了各特征对模型输出的影响。实验结果表明，基于短语一致性图的方法可用于不同的精神疾病检测任务。
英文摘要：
Different state-of-the-art methods of the detection of schizophrenia symptoms based on the estimation of text coherence have been analyzed. The analysis of a text at the level of phrases has been suggested. The method based on the graph of the consistency of phrases has been proposed to evaluate the semantic coherence and the cohesion of a text. The semantic coherence, cohesion, and other linguistic features (lexical diversity, lexical density) have been taken into account to form feature vectors for the training of a model-classifier. The training of the classifier has been performed on the set of English-language interviews. According to the retrieved results, the impact of each feature on the output of the model has been analyzed. The results obtained can indicate that the proposed method based on the graph of the consistency of phrases may be used in the different tasks of the detection of mental illness.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
