Questions tagged [nlp]

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.

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Extracting data from documents

I'm looking for guidance on taking a large documnet such as this clinical study and extracting various pieces of information. For example, I'd like to locate "Exclusion criteria" and extract: On page ...
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89 views

Policy gradient/REINFORCE algorithm with RNN: why does this converge with SGM but not Adam?

I am working on training RNN model on caption generation with REINFORCE algorithm. I adopt self-critic strategy (see paper Self-critical Sequence Training for Image Captioning) to reduce the variance. ...
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84 views

Why did Logistic regression perform better than svm? [closed]

I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G]. I have tried different ML algorithms and found that Logistic regression out ...
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121 views

Will a Count vectorizer ever perform (slightly) better than tf-idf?

For the task of binary classification, I have a small data-set of a total 1000 texts (~590 positive and ~401 negative instances). With a training set of 800 and test set of 200, I get a (slightly) ...
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1answer
42 views

What does localist one-hot vector mean in cs224n NLP course?

Chris said one-hot is a "localist" representation. what does "localist" mean here? I've searched on recommended text, didn't find explanation. any clue?
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24 views

Story Tag Prediction - Optional Labels

I'm currently working on a prediction for fiction. I have a database with fiction, which are each described with different story tags. My idea is to use a neural network that can tell you by ...
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93 views

Output range of BERT model shrinks after fine-tuning on domain specific dataset

My model's sigmoid output range has shrunk after transfer learning with small a dataset. My pretrained model has an output range of 0 to 1. After fine-tuning with a smaller domain specific dataset, ...
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1answer
72 views

How does GlobalMaxPooling work on the output of Conv1D?

In the field of text classification, it is common to use Conv1D filters running over word embeddings and then getting a single value on the output for each filter using GlobalMaxPooling1D. As I ...
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2answers
46 views

Training an acoustic model for a speech-to-text engine

What are the steps for training an acoustic model? The format of the data (the audio) includes its length and other characteristics. If anyone could provide a simple example of how to train an ...
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1answer
29 views

Is there any NLP library or package which can help in adding coma, punctuations, new line appropriately in text?

I have movie transcript, where no coma, punctuations or new line. Is there any NLP technique which can help to implement this?
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91 views

Seq2seq model that gets as input a sentence and outputs the same sentence

I tried to implement a model that takes as input sentences, which are hate_tweets and outputs exactly the same sentences. For this reason, I gave Input to the encoder and decoder exactly the same ...
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1answer
41 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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426 views

Sentence similarity using Doc2vec

I have a list of 50k sentences such as : 'bone is making noise', 'nose is leaking' ,'eyelid is down' etc.. I'm trying to use Doc2Vec to find the most similar sentence from the 50k given a new ...
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18 views

robots.txt communication in webmining

I hope this is the right subforum as I did not really find a suiting one. I'm mining data from a website that does specifically exclude some crawlers from it's site in the robots.txt like this: ...
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19 views

What to use in setting up a Speech to Text engine in production?

So i have the task to study the feasability of setting up a Speech-To-Text engine in a production environnement, and i've been researching on this topic, so I tried Google's Speech-To-Text API and ...
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1answer
31 views

How PV-DBOW works

The authors of the Paragraph Vector paper describe PV-DBOW with: 2.3. Paragraph Vector without word ordering: Distributed bag of words The above method considers the concatenation of the ...
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46 views
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95 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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36 views

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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23 views

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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127 views

Implementing back translation as a data augmentation for text classification

Since back translation English->other language -> English seems like quite a useful data augmentation technique , I wanted to experiment with it. E.g. it occurred to me that languages from very ...
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1answer
153 views

Why does all of NLP literature use Noise contrastive estimation loss for negative sampling instead of sampled softmax loss?

A sampled softmax function is like a regular softmax but randomly selects a given number of 'negative' samples. This is difference than NCE Loss, which doesn't use a softmax at all, it uses a ...
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1k views

How is WordPiece tokenization helpful to effectively deal with rare words problem in NLP?

I have seen that NLP models such as BERT utilize WordPiece for tokenization. In WordPiece, we split the tokens like playing to play and ##ing. It is mentioned that it covers a wider spectrum of Out-Of-...
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1answer
47 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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49 views

What simple machine learning algorithm to use in POS tagging [closed]

I am new to NLP. I have a dataset that has already a parts of speech included, the only problem is what algorithm to use in order to train my dataset. Sample: ...
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73 views

How to use a one-hot encoded nominal feature in a classifier in Scikit Learn?

I'm working on a genre classification problem on a songs dataset. Since genre is a nominal feature, I used sklearn's LabelBinarizer to get the one-hot encoding for this feature for every row in the ...
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1answer
119 views

Automatic labelling of text data based on predefined entities

I'm new to NLP. I have a folder containing .txt files which are legal and specific documents. I want to label all these files based on four predefined labels. How can I do that automatically?
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90 views

Paragraph Generator using BERT or GPT

I am trying to generate similar sentences, called paragraph generation. For example, what is the name of eldest brother of ram? - For this paragraphs can be - who is oldest brother of ram? , Who is ...
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3answers
734 views

Fuzzy name and nickname match

I have a dataset with the following structure: ...
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1answer
82 views

Using the Stanford Named Entity Tagger in R [closed]

I am experimenting with the Stanford Named Entity Tagger here http://nlp.stanford.edu:8080/ner/process and I feel it would be useful in my research. Does anyone know of a example that I could follow ...
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1answer
160 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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1answer
129 views

Detect sensitive data from unstructured text documents

I know this question is broad, but I need an advice to know if it's possible to achieve what I want to do. The problem is that I have around 2500 documents with sensitive data being replaced by four ...
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2answers
44 views

ways to represent document by its keyword vectors

I have documents, say for example, D1, D2, D3... Dm. Every Di has its individual components or keywords k1, k2, k3,... kn, where ki is an n-dimensional vector. The number of individual components ...
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1answer
30 views

Comparing English word pronunciation complexity

I'm trying to figure out a way to compute a score for the pronunciation of a given english word, so I can use that score to compare the pronunciation complexity between english words. Eg: Given ...
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25 views

“Context Resolution” Task in NLP

I'm looking for references to a standard(-ish) task/dataset in NLP that is close(-ish) to the following: we have a document with a list of references (sorry), for example, a scientific paper. For ...
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1answer
48 views

How to create a language translator from scratch?

I want to create a translator which can translate English, Korean and Tamil sentences into English sentence, I tried googletrans but is there any way to create something better than that using DL and ...
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2answers
58 views

Why does the classic Neural Network perform better than LSTM in Sentiment Analysis

My goal is to predict the polarity of some reviews (negative, positive or neutral). I tried two different neural networks: ...
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2answers
51 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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40 views

Error while trying to merge two neural networks

I'm trying to merge two neural networks with Keras. The code: ...
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30 views

NLP: Fuzzy Word/Phrase Match

I am attempting to determine if a given phrase (or a few words) is present in a relatively large text. For example: Text: Lorem ipsum dolor sit amet, consectetur adipiscing elit. Fusce sed ...
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1answer
31 views

What is a better solution for text classification than use of perplexity

To classify some texts, I train a language model over a training set and then select the model which has the lowest perplexity on a given test sample as the class of that sample. I would like to know ...
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24 views

Determine whether or not a company has acquired others using NLP

I'm trying to build a Python script to identify whether a company has acquired others. For this, I intend to seach Google for " acquisition", and parse the titles of the first N pages. Then, from the ...
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16 views

What is the data format of https://wapiti.limsi.fr/?

I have tried using the using CoNLL-U Format, without the pattern file for wapiti (which is supposed to be optional), yet it gives me invalid feature. Would appreciate any kind of guidance.
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1answer
234 views

What to use pretrained models (Glove) or train my own model?

I have been using pre-trained models such as google news or Glove 6B model but many words in my text data does not have their vectors representation in those pre trained model. So I was thinking of ...
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29 views

How can I find the perplexity of a text by the perplexity of its sentences?

For a bigram language model, I can calculate the perplexity of sentences of a test document. However, I'm not sure what would be the perplexity of the whole document. Should I get the average of the ...
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1answer
36 views

How to deal with name strings in large data sets for ML?

My data set contains multiple columns with first name, last name, etc. I want to use a classifier model such as Isolation Forest later. Some word embedding techniques were used for longer text ...
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12 views

Database for faster lookup of string

I have requirement for query database for every possible combination for example. (Have csv file which has name + frequency) Search query : "program java spring project" This will pass to the system ...
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22 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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0answers
57 views

Create word embeddings without keeping fastText Vector file in the repository

I am trying to embed a sentence with the help of Infersent, and Infersent uses fastText vectors for word embedding. The fastText vector file is close to 5 GiB. When we keep the fastText vector file ...
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1answer
76 views

The memorisation capacity of an LSTM (real numbers)

My question is the following: It is known that a LSTM can remember sequences of one-hot encodings which represent integers (i.e. output $x_1, ... x_n$ after receiving $x_1, ... x_n$ as inputs, $x_k \...