update

README.md

@@ -13,11 +13,12 @@ license: apache-2.0
 |    :---     | :---: |   :---:   |       :---:        |   :---:  |     :---:     |     :---:     |
 | enron_spam |  英语  |  垃圾邮件分类  | [enron_spam_data](https://github.com/MWiechmann/enron_spam_data); [Enron-Spam](https://www2.aueb.gr/users/ion/data/enron-spam/); [spam-mails-dataset](https://www.kaggle.com/datasets/venky73/spam-mails-dataset)  | ham: 16545; spam: 17171 |  Enron-Spam 数据集是 V. Metsis、I. Androutsopoulos 和 G. Paliouras 收集的绝佳资源  | [SetFit/enron_spam](https://huggingface.co/datasets/SetFit/enron_spam); [enron-spam](https://www.kaggle.com/datasets/wanderfj/enron-spam) |
 | enron_spam_subset |  英语  |  垃圾邮件分类  |  [email-spam-dataset](https://www.kaggle.com/datasets/nitishabharathi/email-spam-dataset)  | ham: 5000; spam: 5000  |  |  |
-| ling_spam |  英语  |  垃圾邮件分类  |  [email-spam-dataset](https://www.kaggle.com/datasets/nitishabharathi/email-spam-dataset)  | ham: 2172; spam: 433  |  |  |
-|  sms_spam  |  英语  | 垃圾短信分类 | [SMS Spam Collection](https://archive.ics.uci.edu/dataset/228/sms+spam+collection); [SMS Spam Collection Dataset](https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset) | ham: 4827; spam: 747 | SMS 垃圾邮件集合是一组公开的 SMS 标记消息，为移动电话垃圾邮件研究而收集。 | [sms_spam](https://huggingface.co/datasets/sms_spam) |
+| ling_spam |  英语  |  垃圾邮件分类  |  [lingspam-dataset](https://www.kaggle.com/datasets/mandygu/lingspam-dataset); [email-spam-dataset](https://www.kaggle.com/datasets/nitishabharathi/email-spam-dataset)  | ham: 2172; spam: 433  | Ling-Spam 数据集是从语言学家列表中整理的 2,893 条垃圾邮件和非垃圾邮件消息的集合。 |  |
+| sms_spam |  英语  | 垃圾短信分类 | [SMS Spam Collection](https://archive.ics.uci.edu/dataset/228/sms+spam+collection); [SMS Spam Collection Dataset](https://www.kaggle.com/datasets/uciml/sms-spam-collection-dataset) | ham: 4827; spam: 747 | SMS 垃圾邮件集合是一组公开的 SMS 标记消息，为移动电话垃圾邮件研究而收集。 | [sms_spam](https://huggingface.co/datasets/sms_spam) |
+| sms_spam_collection |  英语  |  垃圾短信分类  |  [spam-emails](https://www.kaggle.com/datasets/abdallahwagih/spam-emails)  | ham: 4825; spam: 747  | 该数据集包含电子邮件的集合 | [email-spam-detection-dataset-classification](https://www.kaggle.com/datasets/shantanudhakadd/email-spam-detection-dataset-classification); [spam-identification](https://www.kaggle.com/datasets/amirdhavarshinis/spam-identification); [sms-spam-collection](https://www.kaggle.com/datasets/thedevastator/sms-spam-collection-a-more-diverse-dataset); [spam-or-ham](https://www.kaggle.com/datasets/arunasivapragasam/spam-or-ham) |
 | spam_assassin  |  英语  |  垃圾邮件分类  | [datasets-spam-assassin](https://github.com/stdlib-js/datasets-spam-assassin); [Apache SpamAssassin’s public datasets](https://spamassassin.apache.org/old/publiccorpus/); [Spam or Not Spam Dataset](https://www.kaggle.com/datasets/ozlerhakan/spam-or-not-spam-dataset)  | ham: 4150; spam: 1896 |  数据集从[email-spam-dataset](https://www.kaggle.com/datasets/nitishabharathi/email-spam-dataset)的completeSpamAssassin.csv文件而来。  | [email-spam-dataset](https://www.kaggle.com/datasets/nitishabharathi/email-spam-dataset); [talby/SpamAssassin](https://huggingface.co/datasets/talby/spamassassin); [spamassassin-2002](https://www.kaggle.com/datasets/cesaber/spam-email-data-spamassassin-2002) |
+| spam_base |  英语  |  垃圾邮件分类  |  [spambase](https://archive.ics.uci.edu/dataset/94/spambase)  | 样本个数  |  将电子邮件分类为垃圾邮件或非垃圾邮件  | [spam-email-data-uci](https://www.kaggle.com/datasets/kaggleprollc/spam-email-data-uci) |
 | spam_detection |  英语  |  垃圾短信分类  |  [Deysi/spam-detection-dataset](https://huggingface.co/datasets/Deysi/spam-detection-dataset)  | ham: 5400; spam: 5500  |  |  |
-| sms_spam_collection |  英语  |  垃圾短信分类  |  [spam-emails](https://www.kaggle.com/datasets/abdallahwagih/spam-emails)  | ham: 4825; spam: 747  | 该数据集包含电子邮件的集合 | [email-spam-detection-dataset-classification](https://www.kaggle.com/datasets/shantanudhakadd/email-spam-detection-dataset-classification); [spam-identification](https://www.kaggle.com/datasets/amirdhavarshinis/spam-identification); [sms-spam-collection](https://www.kaggle.com/datasets/thedevastator/sms-spam-collection-a-more-diverse-dataset); [spam-or-ham](https://www.kaggle.com/datasets/arunasivapragasam/spam-or-ham) |
 | spam_message |  汉语  |  垃圾短信分类  |  [SpamMessage](https://github.com/hrwhisper/SpamMessage)  | ham: 720000; spam: 80000 | 其中spam的数据是正确的数据，但是做了脱敏处理（招生电话：xxxxxxxxxxx），这里的 x 可能会成为显著特征。而ham样本像是从普通文本中截断出来充作样本的，建议不要用这些数据。 |  |
 | spam_message_lr |  汉语  |  垃圾短信分��  |  [SpamMessagesLR](https://github.com/x-hacker/SpamMessagesLR)  | ham: 3983; spam: 6990 |  |  |
 | trec_2007 |  英语  |  垃圾邮件分类  |  [2007 TREC Public Spam Corpus](https://plg.uwaterloo.ca/~gvcormac/treccorpus07/); [Spam Track](https://trec.nist.gov/data/spam.html)  | 样本个数  | 2007 TREC Public Spam Corpus | [trec07p.tar.gz](https://pan.baidu.com/s/1jC9CxVaxwizFCvGtI1JvJA?pwd=g72z) |