n-gram

The following word2ngrams function extracts character 3grams from a word: >>> x = 'foobar' >>> n = 3 >>> [x[i:i+n] for i in range(len(x)-n+1)] ['foo', 'oob', 'oba', 'bar'] This post shows the character ngrams extraction for a single word, Quick implementation of character n-grams using python . But what if i have sentences and i want to extract the character ngrams, is there a faster method other than iteratively call the word2ngram() ? What will be the regex version of achieving the same word2ngram and sent2ngram output? would it be faster? I've tried: import string, random, time from

Drupal's core search module, only searches for keywords, e.g. "sandwich". Can I make it search with a substring e.g. "sandw" and return my sandwich-results? Maybe there is a plugin that does that? The most direct module for it is probably Fuzzy Search . I have not tried it. If you have more advanced search needs on a small to medium sized site, Search Lucene API is a fine solution. For a larger site, or truly advanced needs, Solr is the premiere solution. Recently I made a patch for Drupal's core search module to provide it with partial search (aka n-gram searches) ability. This is tested

I am trying to produce a bigram list of a given sentence for example, if I type, To be or not to be I want the program to generate to be, be or, or not, not to, to be I tried the following code but just gives me <generator object bigrams at 0x0000000009231360> This is my code: import nltk bigrm = nltk.bigrams(text) print(bigrm) So how do I get what I want? I want a list of combinations of the words like above (to be, be or, or not, not to, to be). nltk.bigrams() returns an iterator (a generator specifically) of bigrams. If you want a list, pass the iterator to list() . It also expects a

Purpose: I want to create a term-document matrix using a dictionary which has compound words, or bigrams , as some of the keywords . Web Search: Being new to text-mining and the tm package in R , I went to the web to figure out how to do this. Below are some relevant links that I found: FAQS on the tm-package website finding 2 & 3 word phrases using r tm package counter ngram with tm package in r findassocs for multiple terms in r Background: Of these, I preferred the solution that uses NGramTokenizer in the RWeka package in R , but I ran into a problem . In the example code below, I create

I am trying to code dissociated press algorithm based on n-gram in scala. How to generate an n-gram for a large files: For example, for the file containing "the bee is the bee of the bees". First it has to pick a random n-gram. For example, the bee. Then it has to look for n-grams starting with (n-1) words. For example, bee of. it prints the last word of this n-gram. Then repeats. Can you please give me some hints how to do it? Sorry for the inconvenience. Your questions could be a little more specific but here is my try. val words = "the bee is the bee of the bees" words.split(' ').sliding(2)

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: In this documentation , there is example using nltk.collocations.BigramAssocMeasures() , BigramCollocationFinder , nltk.collocations.TrigramAssocMeasures() , and TrigramCollocationFinder . There is example method find nbest based on pmi for bigram and trigram. example: finder = BigramCollocationFinder.from_words( ... nltk.corpus.genesis.words('english-web.txt')) >>> finder.nbest(bigram_measures.pmi, 10) I know that BigramCollocationFinder and TrigramCollocationFinder inherit from AbstractCollocationFinder. While BigramAssocMeasures() and