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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

How to deposit?

Useful links: FAQs | Collection Guidelines | NTU Research Data Management | General terms of use and Privacy policy

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59,521 to 59,530 of 73,650 Results
AllWords.npy
Jul 18, 2020 - All ACM-TWEB Words
Unknown - 724.6 KB - MD5: 696eac49d1c9521c3421a68104338fce
Ordered Bigram Dicts
Jul 18, 2020 - ACM Transactions on the Web
Cheong, Siew Ann, 2020, "Ordered Bigram Dicts", https://doi.org/10.21979/N9/BJSHIR, DR-NTU (Data), V1
npy file containing dictionary of bigrams and their frequencies in each of the 224 ACM-TWEB abstracts.
TWEBOrderedBigramDicts.npy
Jul 18, 2020 - Ordered Bigram Dicts
Unknown - 1.3 MB - MD5: f4ef88f68e2d28477ed2686d66a81626
Ordered Bigrams
Jul 18, 2020 - ACM Transactions on the Web
Cheong, Siew Ann, 2020, "Ordered Bigrams", https://doi.org/10.21979/N9/4GWA8V, DR-NTU (Data), V1
npy file of bigrams ordered from the most frequent to the least frequent for each of the 224 ACM-TWEB abstracts.
TWEBOrderedBigrams.npy
Jul 18, 2020 - Ordered Bigrams
Unknown - 1.2 MB - MD5: 11d5b6751856a2609ed7c4bc05898fdc
Ordered Dicts
Jul 18, 2020 - ACM Transactions on the Web
Cheong, Siew Ann, 2020, "Ordered Dicts", https://doi.org/10.21979/N9/SA1EWV, DR-NTU (Data), V1
npy file containing dictionary of words and their frequencies in each of the 224 ACM-TWEB abstracts.
OrderedDicts.npy
Jul 18, 2020 - Ordered Dicts
Unknown - 525.3 KB - MD5: e39fa1ddadac60d9f3df1e21dc4a8531
Ordered Words
Jul 18, 2020 - ACM Transactions on the Web
Cheong, Siew Ann, 2020, "Ordered Words", https://doi.org/10.21979/N9/GZAHAL, DR-NTU (Data), V1
npy file containing list of words ordered from most frequent to least frequent for each of the 224 ACM-TWEB abstracts.
OrderedWords.npy
Jul 18, 2020 - Ordered Words
Unknown - 466.7 KB - MD5: 423a91057b31313026c2b31c9ce5b0f5
Numpy file
ACM Transactions on the Web(Nanyang Technological University)
Jul 18, 2020The Log Word Rank Movement Method for Keyword Identification
This dataverse contains private datasets on the full text of the ACM Transactions on the Web between 1999 and 2017, as well as public datasets derived from processing these raw datasets.
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