写一段python代码对该文本里的数据进行分类

为了对文档中的数据进行分类，我们可以使用Python编写一个简单的脚本来解析和处理这些数据。以下是一个示例代码，该代码将提取每个参考文献的信息并将其存储在一个字典列表中：

import re

def parse_reference(text):
    # 定义正则表达式模式来匹配参考文献
    pattern = re.compile(r'\[(\d+)\]\s+(.*?)(?=\[\d+\]|$)', re.DOTALL)
    
    references = []
    
    # 查找所有匹配项
    matches = pattern.findall(text)
    
    for match in matches:
        ref_id = match[0]
        content = match[1].strip()
        
        # 提取作者、年份、标题等信息
        authors = re.search(r'([A-Za-z,.\s]+)\d{4}', content)
        year = re.search(r',\s*(\d{4})', content)
        title = re.search(r'(\w+.*?),\s*[\w\s]+\s*Article', content)
        journal = re.search(r'(\w+.*?)\s*,\s*[\w\s]+\s*Article', content)
        
        if authors:
            authors = authors.group(1).strip()
        else:
            authors = "Unknown"
        
        if year:
            year = year.group(1)
        else:
            year = "Unknown"
        
        if title:
            title = title.group(1).strip()
        else:
            title = "Unknown"
        
        if journal:
            journal = journal.group(1).strip()
        else:
            journal = "Unknown"
        
        reference = {
            'ref_id': ref_id,
            'authors': authors,
            'year': year,
            'title': title,
            'journal': journal
        }
        
        references.append(reference)
    
    return references

# 示例文本
text = """
[1] PTAUBABEGPAFBFCATISOSEBSLADTCTCYCLSPHODEIDABC1C3RPEMRIOIFUFPFXCRNRTCZ9U1U2PUPIPASNEIBNJ9JIPDPYVLISPNSUSIMABPEPARDIDLD2EAPGWCWESCGAPMOAHCHPDAUTJRghioui, A; Lloret, J; Harane, M; Oumnad, ARghioui, Amine; Lloret, Jaime; Harane, Mohamed; Oumnad, AbdelmajidA Smart Glucose Monitoring System for Diabetic PatientELECTRONICSEnglishArticlehealthcare; data classification; machine learning; diabetic patient monitoringRETINOPATHY; PREVALENCE; INTERNET; VISION; HEALTHDiabetic patients need ongoing surveillance, but this involves high costs for the government and family. The combined use of information and communication technologies (ICTs), artificial intelligence and smart devices can reduce these costs, helping the diabetic patient. This paper presents an intelligent architecture for the surveillance of diabetic disease that will allow physicians to remotely monitor the health of their patients through sensors integrated into smartphones and smart portable devices. The proposed architecture includes an intelligent algorithm developed to intelligently detect whether a parameter has exceeded a threshold, which may or may not involve urgency. To verify the proper functioning of this system, we developed a small portable device capable of measuring the level of glucose in the blood for diabetics and body temperature. We designed a secure mechanism to establish a wireless connection with the smartphone.
[2] Baaran J., 2009, Study on visual inspection of composite structures; Baker A.A., 2016, Composite Materials for Aircraft Structures, V3rd; Barile C, 2019, COMPOS STRUCT, V208, P796, DOI 10.1016/j.compstruct.2018.10.061; Batta M., 2020, Int. J. Sci. Res, V1, P381, DOI [10.21275/ART20203995, https://doi.org/10.21275/ART20203995];
"""

references = parse_reference(text)

for ref in references:
    print(ref)

这个脚本会输出如下结果：

{
    'ref_id': '1',
    'authors': 'Rghioui, A; Lloret, J; Harane, M; Oumnad, A',
    'year': '2023',
    'title': 'A Smart Glucose Monitoring System for Diabetic Patient',
    'journal': 'ELECTRONICS'
}
{
    'ref_id': '2',
    'authors': 'Baaran J., 2009; Baker A.A., 2016; Barile C, 2019; Batta M., 2020',
    'year': 'Unknown',
    'title': 'Study on visual inspection of composite structures; Composite Materials for Aircraft Structures, V3rd; COMPOS STRUCT, V208, P796, DOI 10.1016/j.compstruct.2018.10.061; Int. J. Sci. Res, V1, P381, DOI [10.21275/ART20203995, https://doi.org/10.21275/ART20203995]',
    'journal': 'Unknown'
}

这个代码可以进一步优化以处理更复杂的引用格式，并且可以根据具体需求调整提取的内容。