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Questions tagged [nltk]

The Natural Language Toolkit is a Python library for computational linguistics.

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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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1answer
27 views

From most frequent words how to extract technical skill words

I've scrape 30 job description web and stored them into a list called job_desc where each item is a job description. ...
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1answer
36 views

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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38 views

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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71 views

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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1answer
75 views

How can I output tokens from MWE Tokenizer?

How to output the tokens produced using MWE Tokenizer? NLTK's multi-word expression tokenizer (MWETokenizer) provides a method/function add_mwe() that allows the ...
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2answers
47 views

Doc2vec '-' symbol occurrence

Currently working on resume parser and struggled with embedding words with '-' symbols in them. Such as 'IT-manager'. Vector representations of these words are incorrectly classified by doc2vec. ['...
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19 views

How to evaluate an ngram on test data?

I created a MLE bigram language model on a text, however, I don't know how to apply it on test data: The following is my try: ...
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1answer
79 views

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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41 views

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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2answers
100 views

How to use bigrams for a text of sentences?

I have a text which has many sentences. How can I use nltk.ngrams to process it? This is my code: ...
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1answer
115 views

Training NLP with multiple text input features

Question: How can I train a NLP model with discrete labels that is based on multiple text input features? Background: I'm trying to predict the difficulty of a 4-option multiple choice exam ...
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67 views

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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3answers
129 views

Machine learning or NLP approach to convert string about month ,year into dates

I'm currently in the process of developing a program with the capability of converting human style of representing year into actual dates. Example : last year last month into December 2018 string may ...
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1answer
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99 views

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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18 views

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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2answers
109 views

Classification: how to handle reviews/long english words in feature set with all other numerical features

I am currently working on an use case where feature set contains numeric values such as amount, as well as a review feature which contains long winded english text. the english text will very well ...
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1answer
62 views

NLP: What are some popular packages for phrase tokenization?

I'm trying to tokenize some sentences into phrases. For instance, given I think you're cute and I want to know more about you The tokens can be something like I think you're cute and I want ...
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83 views

Sentiment analysis with nltk

I'm studying sentimental analysis with python library nltk, following this example: ...
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1answer
54 views

sentiment analysis for multiple entry in one text

I must do sentiment analysis on a set of financial news from s&p500 for given entities (organization names), but the problem is that each news (rows in my dataset) may have more than one entity ...
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2answers
239 views

Python Code to find the number of hapax legomena in a Text or Words_List

In corpus linguistics, a hapax legomenon is a word that occurs only once within a context, either in the written record of an entire language, in the works of an author, or in a single text. The term ...
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4answers
2k views

remove special character in a List or String

Input_String is Text_Corpus of Jane Austen Book output Should be : ['to', 'be', 'or', 'not', 'to', 'be', 'that', 'is', 'the', 'question'] But getting this Output : ['to', 'be,', 'or', 'not', 'to', '...
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1answer
171 views

sentiment analysis nltk python

I'd like to perform sentiment analysis on stock comment using scikit and nltk. I already have about 100 comments on different stocks like "this stock will rock" which I marked as positive (1) or "this ...
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3answers
169 views

Why do we have to remove most common words for text analysis?

I am trying to do sentiment analysis the task is to classify racist tweets from other tweets. And I have read many articles and many have mentioned to remove the most common 10 words from the column ...
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1answer
287 views

Where to know the list of NLTK tagset?

I need to know what the abbreviations mean, e.g 'VBD', 'NN', etc. I am learning text processing and now I want to get verbs in the sentences, so that I need to know which abbreviations represent any ...
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151 views

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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1answer
113 views

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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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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102 views

TextRank using BM25F

I am trying to incorporate BM25F in textrank, I found out a scoring module http://whoosh.readthedocs.io/en/latest/api/scoring.html, but am unable to implement it. Has anyone incorporated this in ...
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1answer
185 views

Is there a synset for phrasal verbs?

Is there a database of phrasal verbs of similar semantics? Eg. one where querying ‘get in touch’ would return ‘get in contact with’, among other phrasal verbs of similar meanings? If not, given a ...
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2answers
105 views

NLP: To remove verb and find the match in a sentence [closed]

Is there a NLP method like stemming, lemmatisation to figure out the below? ...
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0answers
28 views

Predict words in a given corpus from jumbled incomplete characters [closed]

A complete newbie to data science. I have to predict the word using characters given. But the characters given can be in any order, and some might be missing or wrong. The problem is I get too many ...
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1answer
2k views

How to replace short words into full words from tweets using python

I am doing sentiment analysis on tweets. Most of the tweets contains short words and i want to replace them as original/full word. Suppose that tweet is: ...
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120 views

Extracting date, relation and noun phrase from text

A sentence (Segmented from a document) as below: ...
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701 views

How to extract a relation from a Named entity recognition model using NLTK in python

Using this sample article I have created a NLTK model which is able to perform named entity recognition - ...
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2answers
55 views

How to select features for clustering to detect the number of different unique products in a search result?

I am trying to use clustering to determine the number of products in a search of products. So far I am using kmeans clustering. I have run into a problem where I cannot determine good features to use. ...
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1answer
53 views

How to read Feature Based Grammar from a string

To read Context Free Grammars we can use nltk.CFG.fromstring(""" S-> NP VP`... """) But it can't read a feature based grammar which is like? ...
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1answer
181 views

Proper/Possible methods for extracting unstructured data from websites

I'm working in Python, using Scrapy, and NLTK to try to understand how I can extract data from college websites. My scraper can navigate through the university websites and find their tuition fees ...
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1answer
730 views

Why are Chunking and IOB tags necessary?

I've just come across chunking and I can't get my head around why is it necessary? I know that it is used for 'named entity recognition'. I have few questions: Why and how is Chunking helpful? Plus ...
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1answer
34 views

Inappropriate stemming in nltk.stem

I was starting to learn stemming with nltk and a few words were quite inappropriately stemmed. For example:- very was stemmed to 'veri', important to 'import', once to 'onc', poorly to 'poorli' , etc....
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1answer
3k views

How to extract Question/s from document with NLTK?

How to extract Only Question/s from document with NLTK ? Can we categorise this Question into Y/N and details type answerable ? Note: I am one week old in NLTK ;-)
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1answer
679 views

Accuracy of word and sent tokenize versus custom tokenizers in nltk

The Natural Language Processing with Python book is a really good resource to understand basics of NLP. One of the chapters introduces training 'sentence segmentation' using Naive Bayes Classifer and ...
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1answer
1k views

Need help in improving accuracy of text classification using Naive Bayes in nltk for movie reviews

I am referring http://www.nltk.org/book/ch06.html for generating a movie review classifier. It considers all words (Nouns, adjectives, verbs..) as part of feature set. I am trying to build a ...
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2answers
220 views

What is the tag mapping for entity recognition in nltk?

When doing entity recognition using NLTK, one gets as a result a Tree with a bunch of words mapped to tags (eg. Mark -> NNP, <...
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2answers
3k views

StanfordTokenizer will be deprecated in version 3.2.5 Warning

I was testing the StanfordNERTagger using the NLTK wrapper and this warning appeared: ...
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78 views

Search the Number of occurrences of the particular words in data using Pandas.

I wanna Search how many times "bad" and "good" words are repeated in the data frame and visualize this with histogram.
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3answers
1k views

Text Classifier with multiple bag-of-words

I am training an email classifier from a dataset with separate columns for both the subject line and the content of the email itself. I've pre-processed the content column in such a way that the ...
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1answer
80 views

How to go about text mining for suggestions/Tips in reviews for restaurants? [closed]

For example for restaurants reviews usually have suggestions like "Go in the evenings", "order the so and so sauce with this dish" or even "TIP: ask for the blah blah blah" How can I detect such ...