text-mining

问题 I do keyword in context analysis with quanteda for ngrams and tokens and it works well. I now want to do it for skipgrams, capture the context of "barriers to entry" but also "barriers to [...] [and] entry. The following code a kwic object which is empty but I don't know what I did wrong. dcc.corpus refers to the text document. I also used the tokenized version but nothing changes. The result is: "kwic object with 0 rows" x <- tokens("barriers entry") ntoken_test <- tokens_ngrams(x, n = 2,

问题 I do keyword in context analysis with quanteda for ngrams and tokens and it works well. I now want to do it for skipgrams, capture the context of "barriers to entry" but also "barriers to [...] [and] entry. The following code a kwic object which is empty but I don't know what I did wrong. dcc.corpus refers to the text document. I also used the tokenized version but nothing changes. The result is: "kwic object with 0 rows" x <- tokens("barriers entry") ntoken_test <- tokens_ngrams(x, n = 2,

来源： https://stackoverflow.com/questions/32313062/what-is-the-best-way-to-obtain-the-optimal-number-of-topics-for-a-lda-model-usin

来源： https://stackoverflow.com/questions/32313062/what-is-the-best-way-to-obtain-the-optimal-number-of-topics-for-a-lda-model-usin

来源： https://stackoverflow.com/questions/32313062/what-is-the-best-way-to-obtain-the-optimal-number-of-topics-for-a-lda-model-usin

来源： https://stackoverflow.com/questions/49923910/sql-big-query-text-similarity

来源： https://stackoverflow.com/questions/49923910/sql-big-query-text-similarity

来源： https://stackoverflow.com/questions/49923910/sql-big-query-text-similarity

来源： https://stackoverflow.com/questions/48924017/how-do-i-include-stopwordsterms-in-text2vec

来源： https://stackoverflow.com/questions/57395165/extracting-a-persons-age-from-unstructured-text-in-python