In this dataverse, I organized the data files and Python scripts used for developing the Log Word Rank Movement Method for keyword identification.
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Unknown - 17.7 KB - MD5: a2efa2f083b6dcb7fa113b2279274285
Unknown - 15.2 KB - MD5: d31f70e374f85be87ab2a584d4f03ed6
Unknown - 10.5 KB - MD5: 77ea64a93849dad83cf432b468bdfca3
Unknown - 11.0 KB - MD5: bc052c292eb33feab5e52415cf994cf6
Jul 21, 2020 - Python Scripts
Cheong, Siew Ann, 2020, "Statistical Testing of Keywords and Key Bigrams for Reuters News Corpus", https://doi.org/10.21979/N9/A0XM3W, DR-NTU (Data), V1
Python scripts to sample word frequencies from Zipf's Law null model, and to generate histogram for significant and insignificant keywords and key bigrams for Reuters new corpus.
Python Source Code - 4.7 KB - MD5: edb5fea9eb43341e7951d80a5f23b9c6
Python Source Code - 655 B - MD5: ea6b5112c79f66412e90f8dcbff3cbad
Jul 19, 2020 - Python Scripts
Cheong, Siew Ann, 2020, "Histogram of Bigram-Based Agreements Between LWRM2 and RAKE for Reuters News Corpus", https://doi.org/10.21979/N9/ULETZ9, DR-NTU (Data), V1
Python script to plot the histogram comparing the bigram-based agreement between LWRM2 and RAKE for the Reuters news corpus.
Python Source Code - 1.3 KB - MD5: edfcc96f607f9b5d79aa4b4210e18a66
Jul 19, 2020 - Python Scripts
Cheong, Siew Ann, 2020, "Histogram of Bigram-Based Agreements Between TFIDF and RAKE for Reuters News Corpus", https://doi.org/10.21979/N9/Z5CEC5, DR-NTU (Data), V1
Python script to plot the histogram comparing the bigram-based agreement between TFIDF and RAKE for the Reuters news corpus.
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