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用Python代码自动生成文献的IEEE引用格式的实现

这篇文章主要介绍了用Python代码自动生成文献的IEEE引用格式的实现,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧

今天尝试着将引用文献的格式按照IEEE的标准重新排版,感觉手动一条一条改太麻烦,而且很容易出错,所以尝试着用Python写了一个小程序用于根据BibTeX引用格式来生成IEEE引用格式。

先看代码,如下:

import re

def getIeeeJournalFormat(bibInfo):
  """
  生成期刊文献的IEEE引用格式:{作者}, "{文章标题}," {期刊名称}, vol. {卷数}, no. {编号}, pp. {页码}, {年份}.
  :return: {author}, "{title}," {journal}, vol. {volume}, no. {number}, pp. {pages}, {year}.
  """
  # 避免字典出现null值
  if "volume" not in bibInfo:
    bibInfo["volume"] = "null"
  if "number" not in bibInfo:
    bibInfo["number"] = "null"
  if "pages" not in bibInfo:
    bibInfo["pages"] = "null"

  journalFormat = bibInfo["author"] + \
      ", \"" + bibInfo["title"] + \
      ",\" " + bibInfo["journal"] + \
      ", vol. " + bibInfo["volume"] + \
      ", no. " + bibInfo["number"] + \
      ", pp. " + bibInfo["pages"] + \
      ", " + bibInfo["year"] + "."

  # 对格式进行调整,去掉没有的信息,调整页码格式
  journalFormatNormal = journalFormat.replace(", vol. null", "")
  journalFormatNormal = journalFormatNormal.replace(", no. null", "")
  journalFormatNormal = journalFormatNormal.replace(", pp. null", "")
  journalFormatNormal = journalFormatNormal.replace("--", "-")
  return journalFormatNormal

def getIeeeConferenceFormat(bibInfo):
  """
  生成会议文献的IEEE引用格式:{作者}, "{文章标题}, " in {会议名称}, {年份}, pp. {页码}.
  :return: {author}, "{title}, " in {booktitle}, {year}, pp. {pages}.
  """
  conferenceFormat = bibInfo["author"] + \
          ", \"" + bibInfo["title"] + ",\" " + \
          ", in " + bibInfo["booktitle"] + \
          ", " + bibInfo["year"] + \
          ", pp. " + bibInfo["pages"] + "."

  # 对格式进行调整,,调整页码格式
  conferenceFormatNormal = conferenceFormat.replace("--", "-")
  return conferenceFormatNormal

def getIeeeFormat(bibInfo):
  """
  本函数用于根据文献类型调用相应函数来输出ieee文献引用格式
  :param bibInfo: 提取出的BibTeX引用信息
  :return: ieee引用格式
  """
  if "journal" in bibInfo: # 期刊论文
    return getIeeeJournalFormat(bibInfo)
  elif "booktitle" in bibInfo: # 会议论文
    return getIeeeConferenceFormat(bibInfo)

def inforDir(bibtex):
  #pattern = "[\w]+={[^{}]+}"  用正则表达式匹配符合 ...={...} 的字符串
  pattern1 = "[\w]+=" # 用正则表达式匹配符合 ...= 的字符串
  pattern2 = "{[^{}]+}" # 用正则表达式匹配符合 内层{...} 的字符串

  # 找到所有的...=,并去除=号
  result1 = re.findall(pattern1, bibtex)
  for index in range(len(result1)) :
    result1[index] = re.sub('=', '', result1[index])
  # 找到所有的{...},并去除{和}号
  result2 = re.findall(pattern2, bibtex)
  for index in range(len(result2)) :
    result2[index] = re.sub('\{', '', result2[index])
    result2[index] = re.sub('\}', '', result2[index])

  # 创建BibTeX引用字典,归档所有有效信息
  infordir = {}
  for index in range(len(result1)):
    infordir[result1[index]] = result2[index]
  return infordir

def inputBibTex():
  """
  在这里输入BibTeX格式的文献引用信息
  :return:提取出的BibTeX引用信息
  """
  bibtex = []
  print("请输入BibTeX格式的文献引用:")
  i = 0
  while i < 15: # 观察可知BibTeX格式的文献引用不会多于15行
    lines = input()
    if len(lines) == 0: # 如果输入空行,则说明引用内容已经输入完毕
      break
    else:
      bibtex.append(lines)
    i += 1
  return inforDir("".join(bibtex))

if __name__ == '__main__':
  bibInfo = inputBibTex() # 获得BibTeX格式的文献引用
  print(getIeeeFormat(bibInfo)) # 输出ieee格式

下面我来详细说说这个代码怎么使用。

首先,我们需要获取到文献的BibTeX引用格式,可以在百度学术,或者谷歌学术的应用栏中找到,例如这里以谷歌学术举例:

在这里插入图片描述

在搜索框搜索论文:Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application,跳转到以下页面:

在这里插入图片描述

点击“引用”,再点击“BibTex”

在这里插入图片描述

跳转到以下页面,复制所有字符串

在这里插入图片描述

运行我们上面给出的代码,在交互窗口把我们复制的字符串粘贴过去:

在这里插入图片描述

之后点击两下回车,即可得到IEEE格式的文献引用了:

这里我分了会议论文和期刊论文种格式,大家如果想要其他引用格式,可以在我的代码的基础上进行增删改,下面我放一些引用格式转换的例子:

会议论文1:

Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application

BibTeX格式:

@inproceedings{hu2018reinforcement,
title={Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application},
author={Hu, Yujing and Da, Qing and Zeng, Anxiang and Yu, Yang and Xu, Yinghui},
booktitle={Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining},
pages={368–377},
year={2018}
}

IEEE格式:

Hu, Yujing and Da, Qing and Zeng, Anxiang and Yu, Yang and Xu, Yinghui, “Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application,” , in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018, pp. 368-377.

会议论文2:

A contextual-bandit approach to personalized news article recommendation

BibTeX格式:

@inproceedings{li2010contextual,
title={A contextual-bandit approach to personalized news article recommendation},
author={Li, Lihong and Chu, Wei and Langford, John and Schapire, Robert E},
booktitle={Proceedings of the 19th international conference on World wide web},
pages={661–670},
year={2010}
}

IEEE格式:

Li, Lihong and Chu, Wei and Langford, John and Schapire, Robert E, “A contextual-bandit approach to personalized news article recommendation,” , in Proceedings of the 19th international conference on World wide web, 2010, pp. 661-670.

期刊论文1:

Infrared navigation-Part I: An assessment of feasibility

BibTeX格式:

@article{duncombe1959infrared,
title={Infrared navigation—Part I: An assessment of feasibility},
author={Duncombe, JU},
journal={IEEE Trans. Electron Devices},
volume={11},
number={1},
pages={34–39},
year={1959}
}

IEEE格式:

Duncombe, JU, “Infrared navigation—Part I: An assessment of feasibility,” IEEE Trans. Electron Devices, vol. 11, no. 1, pp. 34-39, 1959.

期刊论文2(arXiv):

Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology

BibTeX格式:

@article{ie2019reinforcement,
title={Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology},
author={Ie, Eugene and Jain, Vihan and Wang, Jing and Narvekar, Sanmit and Agarwal, Ritesh and Wu, Rui and Cheng, Heng-Tze and Lustman, Morgane and Gatto, Vince and Covington, Paul and others},
journal={arXiv preprint arXiv:1905.12767},
year={2019}
}

IEEE格式:

Ie, Eugene and Jain, Vihan and Wang, Jing and Narvekar, Sanmit and Agarwal, Ritesh and Wu, Rui and Cheng, Heng-Tze and Lustman, Morgane and Gatto, Vince and Covington, Paul and others, “Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology,” arXiv preprint arXiv:1905.12767, 2019.

到此这篇关于用Python代码自动生成文献的IEEE引用格式的实现的文章就介绍到这了,更多相关Python自动生成IEEE格式内容请搜索以前的文章或继续浏览下面的相关文章希望大家以后多多支持!

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