Questions tagged [nltk]
NLTK is a free, open-source natural language processing toolkit for python. It is used primarily for text processing applications and includes libraries specifically made for classification, tokenization, stemming, tagging, parsing, and semantic reasoning.
33 questions with no upvoted or accepted answers
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Weighting of words in lexicon based sentiment analysis
I am trying to do a lexicon based sentiment analysis on my data, where I calculate the sentiment score as follows:
$$ Score = \frac{\sum_{i}{word_i}}{\mid words \mid} $$
So according to the score the ...
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3
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find bigrams in pandas
I have a DataFrame with 4 columns: 'Headline', 'Body_ID', 'Stance', 'articleBody', with 'Headline' and 'articleBody containing cleaned and tokenized words. I want to find bi-grams using nltk and have ...
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133
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multiple intents for modifying an intent of a sentence?
Say I have a sentence like 'I refuse to fly' or 'I'd like to fly'. I also have a sentence like 'I don't want to sit'. When training custom intents in one of the available NLU engines (rasa/wit/luis), ...
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Looking for a generalized (extended) lemmatizer
Whenever I lemmatize a compound word in English or German, I obtain a result that ignores the compound structure, e.g. for 'sidekicks' the NLTK WordNet lemmatizer returns 'sidekick', for '...
2
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298
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Text preprocessing on corpus in pipeline before Gensim word2vec training
I have a large compressed corpus, about 30gb in .txt.gz format. In raw format it can be used as input to word2vec like this:
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2
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882
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improve NER model accuracy with spaCy dependency tree
I have search at lot, was not able to find a solution for my problem...
I am training a NER model, that should detect two types of words: Instructions and Conditions. This is not the standard use-case ...
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2
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115
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Text extraction / mining from specific templates (ML)
believe me if I say that I have read basically all the threads in this website regarding this subject. A lot of them have a similar title, but the problem is somehow different.
Small context: just ...
- 121
2
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1
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633
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How to find possible subjects for given verb in everyday object domain
I am asking for tools (possibly in NLTK) or papers that talk about the following:
e.g. Input: Vase(Subject1) put(verb)
Ans I am looking for: flower, water
Is there a tool that can output subjects (...
2
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0
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267
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Extracting date, relation and noun phrase from text
A sentence (Segmented from a document) as below:
...
- 121
2
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0
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181
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Data categorization
I'm using Google API to categorize and predict problems with laptops (Hardware, Software, Network, Customer satisfaction, No reason). I inserted my training data and categories are very well evaluated ...
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Which Pointers from WordNet are Used for Synset in NLTK
I'm trying to create a custom parser for wordnet and hit a roadblock. I see that there are tons of different pointer_symbols and lots of them seem almost like synonyms but not exactly synonyms. I'm ...
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2
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Need help to increase classification accuracy for classified ads posting
I have to predict the category under which ad was posted using the provided data; I cannot gain accuracy more than 74% for my model. I am not sure what I am missing.
What I have done so far:
Cleaned ...
- 21
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0
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41
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How to find the related columns between column?
Suppose I have a data frame with columns car_id,number_car,bike_id,number_bike.
...
1
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1
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525
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train NER using NLTK with custom corpora (non-english) must use StanfordNER?
I have searched about customization NER corpora for trainig the model using NLTK library from python, but all of the answer direct to nltk book chapter 7 and honestly makes me confuse how to train the ...
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For short sentences(max length 10 ), which Name entity recognition algorithm is good?
My Training data look like this .
I have to recognize 4 class for each sentence.
Any algorithm , which have some learning parameters Means not rule based approach . So which method is good for my ...
- 11
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Semi-Supervised Learning using NLP
I am working on a drug reaction problem in which I need to extract tweets and label the tweets (binary-reaction due to drug or not). But since I don't have domain knowledge, and clustering would also ...
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Manipulate the nltk.word_tokenize to remove the stopwords and assign to two dataframe
I'm trying to manipulate an imported list of keywords with about 1000 factors from a CSV, tokenizing the list while, at the same time, removing the stop words.
A dedicated function, returning a tuple, ...
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Determining topic of text
I was wondering what I should be looking into if I want to measure the similarity between a paragraph and a corpus of text.
For example, given a paragraph of text and the entire corpus of Data ...
- 71
1
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1
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828
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Elbow method for cosine distance
I have clustered vectors by cosine distance using nltk clusterer. If I understand correctly, Y axis for elbow method in euclidian distance would be the sum of every distance (squared) between centroid ...
- 111
1
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293
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How can I find colors in a sentence?
Given a sentence "I like blue jeans", the output should be "blue".
I do not have any training data. I'll just be downloading a bunch of tweets related to a hashtag.
How do I build a model for this? ...
- 11
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2
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777
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Unable to resolve Type error using Tokenizer.tokenize from NLTK
I want to tokenize text data and am unable to proceed due to a type error, am unable to know how to proceed to rectify the error, To give some context - all the columns - Resolution code','Resolution ...
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198
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Named Entity Recognition using context of the sentence
I have a problem in which I want to know how can we extract or name the entity based on the context in which it is getting used in a sentence.
For example:
If we have to extract date field which is ...
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2k
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How can I calculate perplexity for a bigram model?
I didn't find any function in nltk to calculate the perplexity.
There are some codes I found:
...
- 427
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107
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Feature matrix for email classification:
This is in continuation of my earlier post.
In my previous model, I used just two features which couldn't fare well and gave 71% prediction (accuracy) score. Now, I'm trying to consider another ...
- 451
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Installing NLTK using WHL file -
I have previously used WHL (wheel) files to install various Python packages. But, it seems there's no such file for NLTK. Any workaround for this please?
https://pypi.org/project/nltk/
The problem ...
- 451
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36
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Automating scoring of answers for a given question
There is a topic 'X' on which students are asked to write an English passage. Given a question, I have multiple solutions with their scorings out of 10.
For a given answer by a new candidate, one ...
- 111
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2
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1k
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What would be the best way to map similar ngrams
I'm trying to map similar ngrams using Wordnet and synsets. For example: elder brother and older sibling should map to the same ...
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40
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Tuning Lexicon Sentiment-values Using Machine-learning
I'm constructing a sentiment-analysis model using the lexicon-based approach, and wondering if I can tune the weights of each word-feature in the lexicon using machine-learning. Is this achievable ...
- 111
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223
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How to dowload Wikileaks Cable Leaks documents as text corpus?
I'd like to perform NLP analysis on Wikileaks US Diplomatic Cable Leaks documents (https://wikileaks.org/plusd/), preferably as Python's NLTK3 corpus od Mongo DB documents. I couldn't find any option ...
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268
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NLP : What are some common verbs surrounding organization names in text
I am trying to come up with some rules to detect named entities, specifically company or organization names in text. I think it makes sense to focus on verbs. There are a lot of ...
- 378
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Error while using NLTK/ How should I read paragraph using NLTK?
I am a total newbie. I have a custom text document which is a paragraph. I am trying to read it and display using NLTK.
following is my code;
...
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887
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What is "Interpolated Absolute Discounting" smoothing method
I'm asked to implement "Interpolated Absolute Discounting" for a bigram language model for a text. First, I don't know what is it exactly. I guess it is an interpolation between different ngrams (...
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1
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Building a text extractor to extract particular type of text from unstructured text data
I have a lot of data and manually extracted annotations for the text. I was looking for any advice to automate the annotation extraction up to a good level of accuracy. Any advice is welcome.
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