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Adobe PDF - 1.0 MB -
MD5: 23db1878d091706ee16939f1608b0bb5
PDF of Powerpoint slides explaining how to use R to analyze CGED-Q JSL |
Adobe PDF - 826.4 KB -
MD5: 7d3862936a0c04bada87e961ff6b95cd
PDF of Powerpoint slides explaining how to use R to analyze CGED-Q JSL |
Adobe PDF - 1015.2 KB -
MD5: 8bd191478ec61ad6c2efe38a00b66e28
PDF of Powerpoint slides explaining how to use R to analyze CGED-Q JSL |
Adobe PDF - 1.9 MB -
MD5: 9e8232bf896924d6fe1b50ba0c80a8b2
PDF of Powerpoint slides explaining how to use R to analyze CGED-Q JSL |
R Notebook - 172.2 KB -
MD5: d86663a1989daf2fb424119837df7f79
R markdown file with tutorials for using R to analyze the CGED-Q. By Chen Jun. |
Adobe PDF - 14.6 MB -
MD5: d91a024523a640eba136772838ca1eab
PDF of output from R Markdown file tutorial for using R to analyze the CGED-Q. By Chen Jun. |
Jul 10, 2025 - HKUST Library Digital Scholarship CoLab Projects
HKUST Library - Digital Scholarship, 2025, "Tales from a 1493 World Map: Playing with AR", https://doi.org/10.14711/dataset/CHHXX8, DataSpace@HKUST, V1
Our Library’s Special Collections contains remarkable collections of antique maps. These maps are not just historical artifacts – they are stories waiting to be told. In a digital age where technology shapes our interactions with information, we have an opportunity to enhance the... |
Jul 10, 2025 -
Tales from a 1493 World Map: Playing with AR
ZIP Archive - 228.3 MB -
MD5: dac0b4ee592831a319592a0cc0e4a7f2
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Adobe PDF - 2.6 MB -
MD5: 78e3877b9e2eab8442766c8a2679d9c8
User Guide updated to reflect 2024 release of 1760-1798 data, as well as new information about the source. |
May 27, 2025 - HKUST Library Digital Scholarship CoLab Projects
HKUST Library - Digital Scholarship, 2025, "Chinese Named-Entity Recognition (NER) Tool", https://doi.org/10.14711/dataset/B6IUMG, DataSpace@HKUST, V1
Named-Entity Recognition (NER) is a natural language processing technique that can automatically identify and categorize key elements such as people, organizations, locations, dates, and other important concepts within a large amount of text. This technique enables researchers to... |
