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.
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Weighting of words in lexicon based sentiment analysis
I have a a question regarding my current project, i am trying to do a lexicon based sentiment analysis on my data, where i calculate the sentiment score as following:
$$ Score = \frac{\sum_{i}{word_i}...
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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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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 '...
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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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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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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 ...
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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 (...
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Extracting date, relation and noun phrase from text
A sentence (Segmented from a document) as below:
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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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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 ...
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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.
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How do I split contents in a text that would include two or more different themes (context) in NLP?
For example, a text: "The airlines have affected by Corona since march 2020 a crime has been detected in Noia village this morning"
the output should be:
The airline companies have affected ...
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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 ...
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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 ...
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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 ...
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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? ...
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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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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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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:
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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 ...
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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 ...
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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 ...
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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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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 ...
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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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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 ...
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Trying to compress text with NLP
For a university project, I need to send text in Spanish via SMS. As these have a cost, I am trying to compress this text in an inefficient way. This consists of first generating a permutation of ...
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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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nltk.corpus for data science related words?
from job description I scraped from the internet, I've went through all nlp processes and I've got to place where I found:
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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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NLP how to go beyond simple intent finding--using context and targeting objects
I'm manually applying NLP rules to a chatbot.
Currently, I've a simple set of rules--actions that follow certain trigger words.
Ex: "Create the match on saturday."
This has been working for ...
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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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