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Questions tagged [natural-language-process]

Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human–computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input, and others involve natural language generation. See NLP.

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How do I visualize data for a natural language processing project?

I am using a question-and-answer dataset. My neural network takes a question and an article content, and outputs where an answer starts (as an integer). To visualize my data, how should I process it ...
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What are tokens and tokenizations?

I'm a high school senior who is new to data science, and would like to get into natural language processing. I currently know nothing about NLP, and the information online can be overwhelming. What ...
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Categorization of Natural Language Processing Tasks

Problem I am currently learning basics of natural language processing. I see many tasks in this area is assigning labels to each individual words in the sentence, including POS tagging, chunking, ...
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Natural language Generator using Data from table

I am working on some natural language generator part. eg.1 Input to it will be Col1 Col2 Col3 A B 13 X Y 14 Output should be two sentence, one ...
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25 views

How to replace words in a sentence with their POS tag generated with SpaCy efficiently?

How is it possible to replace words in a sentence with their respective PoS tags generated with SpaCy in an efficient way?
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19 views

Reading a visualization of word embeddings

For my Masters Thesis, I created a Word2Vec model. I wanted to show this image to clarify the result. But how does the mapping works to display the words in this 2D space? All words are represented ...
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What is the use of [SEP] in paper BERT?

I know that [CLS] means the start of a sentence and [SEP] makes BERT know the second sentence has begun. However, I have a question. If I have 2 sentences, which are s1 and s2, and our fine-tuning ...
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How do I go about performing unsupervised topic and opinion extraction from free-text?

I have a few 1-column datasets of free-text taken from 1000-1500 users in a survey. They were asked to write whether they would recommend a certain company/product, and their reason for it. A small ...
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How to decide between using machine learning and deep learning for a NLP classification problem?

I have a classification problem at hand for which I tried out some traditional ML models to get a glimpse of what I get as results. Brief description of the BINARY classification problem: I have a ...
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Make top N word predictions using a character model?

Given a character model that can predict (in addition to typical ascii characters) a special end-of-word character, I can make a word prediction by iteratively appending character predictions to my ...
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LSTM input and output for sentiment analysis

I'm studying this LSTM network: https://www.kaggle.com/paoloripamonti/twitter-sentiment-analysis ...
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How should I treat these non-English documents in the NLP task?

So I have a small corpus of about 30k documents and about 50 documents in this corpus are in other languages (Persian, Chinese, Arabic, German, Spanish etc). I will be using this corpus for training a ...
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Using Keras how and what do I need to export to use my classifier independently?

I have a basic question that I can't seem to find an answer to. I built and trained with good results (above 90% accuracy) a NLP Log classifier that takes in a UTF-8 payload and classifies it into 32 ...
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Need help with entity tagging

I need to design a system which can identify movie and production company names in a sentence. The approach that comes to my ...
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How can I categoriese / classify a cluster of words?

I am just wondering if it is possible to classify word clusters? For example if I provide you an array of words [bird,chicken,dock,park,apple,grapes,furits,juice] ...
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*Challenge* Making an algo that learns from a book, and can answer anything about it

I recently took this challenge where I am trying to make a set of algorithms to read any particular book, understand and store the context and subsequently answer any question asked about it. In ways ...
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Lemmatization Vs Stemming

I have been reading about both these techniques to find the root of the word, but how do we prefer one to the other? Is "Lemmatization" always better than "Stemming"?
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How to byte-pair encode character sequences at prediction time?

Suppose I have a vocabulary V = {'f', 'o', 'b', 'a', 'r', 'fo', 'ob', 'ar', 'foob', 'obar'} from BPE and at prediction time I come across an input ...
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21 views

How to do Natural Language Processing with few samples only?

I am familiar with SMOTE (Synthetic Minority Oversampling), and the Python Library imbalanced-learn, which can be used to handle ...
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How does BERT deal with catastrophic forgetting?

In the ULMFit paper authors propose a strategy of gradual unfreezing in order to deal with catastrophic forgetting. That is, when the model starts be fine-tuned according to a downstream task, there ...
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Are these Multi-label document classification experiment steps sensible?

I plan to filter an input document using 4 different labels. Just for an example, a document discussing about movie summary needs to be labeled with 4 labels (Romance, Drama, Fiction, Hollywood). ...
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How can I find colours 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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1answer
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How to cluster text-based software requirements

I'm beginner in deep learning and I'd like to cluster text-based software requirements by themes (words similarities/frequency of words) using neural networks. Is there any example/tutorial/github ...
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1answer
35 views

Why Heaps' Law Equation looks so different in this NLP course?

I'm actually not sure if this question is allowed on this community since it's more of a linguistics question than it is a data science question. I've searched extensively on the Web and have failed ...
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Doc2vec most similar document to a query string

I'm working on a project and I created doc2vec representation of different academics which include their patents and publications etc. For each publication and patent I have information such as title ...
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Implementation of NLP to categorize text into two categories

I can't discuss my actual dataset, so please bear with me. Let's say I have a dataset that contains a population of 20,000 examinations by a school principal. The principal is to record their ...
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Given an input phrase, is there a way I can find the most similar phrase within a document?

I am completing a task where I need to retrieve the corresponding values to a set of given labels from many legal contracts. For example, one of the labels is "Floating rate payment dates" and it's ...
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Why is MLP working similar to RNN for text generation

I was trying to perform text generation using only a character level feed-forward neural network after having followed this tutorial which uses LSTM. I one-hot encoded the characters of my corpus ...
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What are CRF (Conditional Random Field)

Looking for language modeling, I have been finding CRF in a lot of places which is but looking online for the same isn't actually helping me a lot. I referred Edwin Chen's blog and Ravish Chawala's ...
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45 views

How to calculate which word fits the best given a context and possible words?

I have this task for research purposes and searched a while for a framework or a paper which already took care of this problem. Unfortunately I don't find anything which helps me with my problem. I ...
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1answer
60 views

Which is better: GPT or RelGAN for text generation?

Based on my understanding, gpt or gpt-2 are using language model loss to train and generate text, which do not contains GAN. So which is better: GPT vs RelGAN/LeakGAN/SeqGAN/TextGAN I am so ...
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29 views

How to prepare the data for text generation task

First, I'm not sure whether the model contains the encoder during training. EOS means end-of-sentence. Encoder and decoder are part of transformer network. If without-encoder, training time: ...
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1answer
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The principle of LM deep model

Language model(LM) is the task of predicting the next word. Does the deep model need the encoder? From the ptb code of tensor2tensor, I find the deep model do not contains the encoder. Or both with-...
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What is the difference between TextGAN and LM for text generation?

I'm new to LeakGAN or SeqGAN or TextGAN. I know GAN is to generate text and let discriminator un-judge-able to real text and gen-text. LM(language model) is the task of predicting the next word and ...
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Clustering and graphing similarities of sentence subjects

I have a bunch of sentences. Each sentence is given a weight of how "close" it is to a particular subject. Ex. "I love reading math books" Subjects for the above sentence = ...
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NLP to recognize the meaning of a paragraph

How can I apply NLP to extract the summary of a paragraph,I found this but was wondering if there is a better and easy way before implementing it, as the ans seems to be an old one. Basically what I ...
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Hierarchical softmax for prediction

Original paper: https://www.iro.umontreal.ca/~lisa/pointeurs/hierarchical-nnlm-aistats05.pdf I understand that during training (say for text generation), only the probability of the target word (...
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1answer
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Is there a way to cluster words based on how similarly they sound?

I have a list of words for a fictional world I've made (don't judge lol). My ultimate goal is to generate more words that sound like them through a markov generator, but for now, I'm trying to build ...
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Can Amazon Comprehend (Medical) be used for autocompletion of words or phrases?

"Amazon Comprehend Medical can accurately identify abbreviations, misspellings, and typos in medical text" source here. As such I believe one could use it to develop an autocorrect service, that ...
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Is there any text similarity databse available for phrases?

I want to train my application for phrase similarity. I want my model to predict similarity score for phrases as shown in below examples. ex- ...
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How is maximizing L(lambda1, lamda2, lamda3) equivalent to minimizing perplexity?

In language modeling, L(lambda1, lambda2, lambda3) is defined as: Sum(count of trigram(u,v,w) x q(w|u,v)) where u, v, w are words in the corpus and perplexity ...
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Trying to implement a “smart compose” feature

I found this post on Gmail's smart compose feature, and it got me thinking about trying to implement it myself. https://ai.googleblog.com/2018/05/smart-compose-using-neural-networks-to.html The text ...
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How to extract name of objects from technical description (NLP)

I have a list of technical descriptions of mechanical parts such as Relay Compressor A4u8skk Relay-Start-Compressor sdfvsh2 Relay-Start-Compressor-Copelan 05-569-21 Compressor-J4KS0AK-5gss-fj2 ...
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Identify specify areas in the text

I'd be interested in identifying various areas in the text message. Let's say I have a text containing some introduction, then there is a poem and at the end there are some urls to some web pages. I'...
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Word classification (not text classification) using NLP [closed]

I have been trying to extract Person name and Company name out of string. But, I have been facing lot of difficulties. I have a dataset of names and a dataset of company names. In the string, I wish ...
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Replacement for English Wizard

I am using the English Wizard to access the SQL database. Is there any other 3rd party tool similar to the English Wizard that will work on web and desktop application?
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Job Recommendation System

I am building a Job Recommendation System where I have Student Data for different subjects in Machine Learning(Data Viz, Python, Statistics, etc) and their skills from the resume. Need to Recommend ...
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3answers
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Which neural network to choose for classification from text/speech?

I am considering two tasks: Dialog Act Classification from Text (e.g. classify to: question; opinion; ...) Emotion Recognition from Speech (e.g. happy; calm; sad; ...) Which DL model should perform ...
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Continous bag of words claimed to be unsupervised, how is it working?

I'm following these two lectures on CBOW and skip-gram word2vec models. The first is lec 12 and the next lec 13 of a deep learning series https://www.youtube.com/watch?v=syWB-YMYZvI https://www....
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Updating Google News Word2vec Word Embedding?

Is it possible to update the Google News Word Embedding with a custom text dataset (text data pertaining to a particular domain) ? Google News Word2Vec - Word Embedding clearly helps us to come with ...