论文标题
基于短语的一致性来评估文本连贯性，以鉴定精神分裂症的症状
Evaluating text coherence based on the graph of the consistency of phrases to identify symptoms of schizophrenia
论文作者
论文摘要
已经分析了基于文本连贯性的估计，检测精神分裂症症状的不同最新方法。已经提出了对短语级别的文本的分析。已经提出了基于短语一致性图的方法来评估语义连贯性和文本的内聚力。已经考虑了语义连贯性，内聚力和其他语言特征（词汇多样性，词汇密度），以形成特征向量以训练模型分类器。分类器的培训已在英语访谈中进行。根据检索到的结果，已经分析了每个特征对模型输出的影响。获得的结果可以表明，基于短语一致性图的提议方法可用于精神疾病检测的不同任务。
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.
