Elasticsearch: Find substring match
autocomplete,elasticsearch,substring,stringtokenizer,n-gram
TO search for partial field and exact match.You better define the fields as not analyzed.And then use wildcard query.[not analyzed will reduce cpu usage During indexing.] To mentions some field as not analyzed refer this To use wildcard query append * on both end of string you are searching for...
EdgeNGramFilterFactory is not working fine in solr
solr,indexing,n-gram,search-suggestion
First thing : solr.EdgeNGramFilterFactory doesn't work popular on the suggestions we get in the suggestion block. Suggestions are coming by default using class="solr.SpellCheckComponent" solr.EdgeNGramFilterFactory works on the response /result that comes from the query which we ask. Second : MaxResultForSuggest = value. where value may be 10 (integer) If...
Polynominal error in Rapidminer when doing n-gram classification
svm,libsvm,n-gram,rapidminer,concept
You have to use the Support Vector Machine (LibSVM) Operator. In contrast to the classic SVM which only supports two class problems, the LibSVM implementation (http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf) supports multi-class classification as well as regression.
Multi-word Term Vectors with Word nGrams?
Assuming you already know about the Term Vectors api you could apply the shingle token filter at index time to add those terms as independent to each other in the token stream. Setting min_shingle_size to 1 (instead of the default of 2), and max_shingle_size to at least 3 (instead of...
What is the most efficient way of storing language models in NLP applications?
The most common data structures in language models are tries and hash tables. You can take a look at Kenneth Heafield's paper on his own language model toolkit KenLM for more detailed information about the data structures used by his own software and related packages.
Really fast word ngram vectorization in R
This is a really interesting problem, and one that I have spent a lot of time grappling with in the quanteda package. It involves three aspects that I will comment on, although it's only the third that really addresses your question. But the first two points explain why I have...
n grams scala output set transformation
It's the type signature for op2. You could do remove the assignment to Op2 ngrams(3, "how are you".split(" ")).foreach { x => println((x.mkString(" ")))} Change .foreach to .map and the call op2 for the result. scala> val op2 = ngrams(3, "how are you".split(" ")).map { x => x.mkString(" ")}.toList scala>...
Possible to write bigram (or ngram) function using reduce in Javascript?
javascript,functional-programming,reduce,n-gram
The way reduce works is that the output of one call is used as the input to the next call. If we name your function f, your call is equivalent to: f(f(f(f(0, 1), 2), 3), 4) In other words, the previous does not mean "previous item in the original array",...
How to sort list of string by n-grams in python
Assuming that by "descending order of n-grams" you mean that you want to have, e.g. first all the 3-grams, then the 2-grams, etc., you can try this: >>> ngrams = ["sedan", "sail sedan", "sail", "price of", "price", "of chevrolet", "of", "chevrolet sail", "chevrolet"] >>> sorted(ngrams, key=lambda s: len(s.split()), reverse=True) ['sail...
Detecting foreign words
If your method is returning words present in both languages, and you only want to return words that exist in one language, you might want to create a list of one-grams in language A and one-grams in language B, and then remove the words in both. Then, if you like,...
Python NLTK: Bigrams trigrams fourgrams
If you apply some set theory (if I'm interpreting your question correctly), you'll see that the trigrams you want are simply elements [2:5], [4:7], [6:8], etc. of the token list. You could generate them like this: >>> new_trigrams = [] >>> c = 2 >>> while c < len(token) -...
How to get word trigrams in elasticsearch
curl,lucene,elasticsearch,n-gram
Found it. Answer lies in the shingle filter. This mapping made it work { "settings": { "analysis": { "filter": { "nGram_filter": { "type": "shingle", "max_shingle_size": 3, "min_shingle_size": 3, output_unigrams:false } }, "analyzer": { "nGram_analyzer": { "type": "custom", "tokenizer": "whitespace", "filter": [ "lowercase", "asciifolding", "nGram_filter" ] }, "whitespace_analyzer": { "type": "custom",...
CoreNLP API for N-grams?
nlp,stanford-nlp,n-gram,pos-tagger
If you are coding in Java, check out getNgrams* functions in the StringUtils class in CoreNLP.
What is the total bigram count returned for NLTK BigramCollocationFinder?
First we dig out the score_ngram() from nltk.collocations.BigramCollocationFinder. see https://github.com/nltk/nltk/blob/develop/nltk/collocations.py: def score_ngram(self, score_fn, w1, w2): """Returns the score for a given bigram using the given scoring function. Following Church and Hanks (1990), counts are scaled by a factor of 1/(window_size - 1). """ n_all = self.word_fd.N() n_ii = self.ngram_fd[(w1, w2)]...
How do I create a generic type parameterized by a number?
It will be possible in the future, but until then, the best way to do it is: Use a base trait for a fixed size array, implement it with macros for all the sizes you need. With the trait, you don't need more macros for the rest of the functionality....
Solr ngram does not match the terms with special chars
<filter class="solr.PatternReplaceFilterFactory" pattern="([^\w\d\*æøåÆØÅ ])" replacement="" replace="all" /> This would delete most of the unusual characters. So, that's probably your problem. Try commenting it out and seeing what you get. But in general, you can look at the analysis screen of the Web Admin UI and see how the text...
How to pass in an estimator to NLTK's NgramModel?
python,nlp,nltk,n-gram,linguistics
Currently, you can use a lambda function to return the Freqdist from a distribution, e.g. from nltk.model import NgramModel from nltk.corpus import brown from nltk.probability import LaplaceProbDist est = lambda fdist: LaplaceProbDist(fdist) corpus = brown.words(categories='news')[:100] lm = NgramModel(3, corpus, estimator=est) print lm print (corpus[8], corpus[9], corpus[12] ) print (lm.prob(corpus[12], [corpus[8],...