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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454 views

BERT classifier with Ktrain API is unable to predict new data

I have trained a classifier for sentiment analysis using BERT architecture. I am able to train the classifier and I am getting a validation accuracy of 87%. But whenever I feed in test data, or some ...
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25 views

Looking for a causality to effect dataset

I am looking for a causality dataset that would look like this: ...
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1answer
29 views

Determining whether a sentence is “cliche” using NLP

I have a collection of essays from students. Each essay is about the same topic and of the same word length. My goal is to develop a machine learning algorithm that pinpoints "cliche" ...
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1answer
28 views

How to identify word in a sentence representing the song genre?

I am training a model to identify a word that represents a song genre given a sentence. For example, the model is given a sentence "Beethoven songs are part of the classical genre." The model will ...
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1answer
18 views

Is LSTM or pretrained BERTForMasked LM usable for predicting changed word in a sentence using a small dataset? (2000 samples)

I have a small (2000 samples) dataset of newspaper headlines and their humorous conterparts where only one word is changed to sound silly, for example: Original headline: Police <officer> ...
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1answer
108 views

KeyError: Selecting text from a dataframe based on values of another dataframe

I have the following two dataframes badges and comments. I have created a list of 'gold users' from ...
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20 views

Search for similar wikipedia articles based on a set of keywords [closed]

I want to solve two questions: Which wikipedia articles could be interesting to me based on a list of keywords that are generated by the search terms I normally use in google(received by google ...
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1answer
79 views

How to generalize comments using NLP

I have list of log comments in CSV file. I want to cluster those log comments using K-Means and after that I want convert each cluster comments into general form. for eg. I have bunch of comments in ...
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1answer
44 views

How to deal with class imbalance problem in natural language processing?

I am doing a NLP binary classification task, using Bert + softmax layer on top of it. The network uses cross-entropy loss. When the ratio of positive class to negative class is 1:1 or 1:2, the model ...
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1answer
27 views

Preparing training data for NLP machine learning task

I have the natural language sentences as follows: This is a black chair. It is next to the table. Each phrase that represents an object is annotated with an object ...
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1answer
49 views

Emotional tension score in sentences

I am beginner in natural language processing and my goal is to find a way to score sentences based on their emotional tension. More specifically, I would like to know to what degree a sentence ...
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39 views

Difference between NCE-Loss and InfoNCE-Loss

I started looking into word2vec and was wondering what the connection/difference between the NCE-Loss and the infoNCE-Loss is. I get the basic idea of both. I have a hard time deriving one from ...
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63 views

Word2Vec: Why do some dimensions of an embedding have an interpretation, and why does addition/subtraction of embedding vectors work?

I'm reading about Word2Vec from this source: http://jalammar.github.io/illustrated-word2vec/. Below is the heatmap of the embeddings for various words. In the source, it's claimed that we can get an ...
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77 views

Which machine learning problem is this?

I am not able to figure out what kind of machine learning is this: Training set: consists of sentences with object labels for object phrases Example: ...
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1answer
35 views

Generate text using user-supplied keywords

I've got a use case where I need to generate sentences based on a set of user supplied keywords. Here is an example of what I need: User input: End-User: Data Scientists Region: Middle East ...
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1answer
64 views

Semantic network using word2vec

I have thousands of headlines and I would like to build a semantic network using word2vec, specifically google news file. My sentences look like ...
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2answers
3k views

Why is the decoder not a part of BERT architecture?

I can't see how BERT makes predictions without using a decoder unit, which was a part of all models before it including transformers and standard RNNs. How are output predictions made in the BERT ...
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11 views

Language Model with Attention not learning

Language model with attention layer is not learning after 20 epochs. Both training and validation loss increase together, while the accuracy flattens at around 7% The way input data is pipelined is by ...
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23 views

Training a Supervised Classifier using Continuous Data

I am trying to build a NLP classification model using methods such as XGBoost, SVM, logistic regression. The features I am trying to include are cosine similarity and LDA topic models, all of which ...
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1answer
16 views

Difference between zero-padding and character-padding in Recurrent Neural Networks

For RNN's to work efficiently we vectorize the problem which results in an input matrix of shape (m, max_seq_len) where m is the number of examples, e.g. ...
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2answers
74 views

State-of-the-art Python packages that can evaluate language similarity

I am trying to evaluate the likelihood of generating a specific sentence out of a large set of sentences. To do this, I start from a simple approach: training a custom n-gram language model and ...
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6 views

Multilingual alternatives for med7

I'm looking for alternatives for med7 library for other common languages. Training a custom NER model for different languages seems like not the right option to ...
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93 views

Is NLP suitable for my legal contract parsing problem?

My company has a product that involves the extraction of a variety of fields from legal contract PDFs. The current approach is very time consuming and messy, and I am exploring if NLP is a suitable ...
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1answer
70 views

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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38 views

Learning words embedding for bigrams and unigrams in a corpus

I am working on a topic modeling for tweets projects. I have generated my topics using both unigrams and bigrams. Topics are defined with a mixture of both bigrams and unigrams. Now I am planning to ...
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4answers
52 views

Pre-trained models

I am starting off with machine learning so could someone tell if there is some site where one can find the current best performing trained models for any specific problem like sentiment analysis or ...
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1answer
681 views

Text analysis - classification, parsing

Excuse if this has been answered before. I need to extract features and parse from a piece of text and run some analysis. For e.g. "Plot the past 5-year sales of Apple" should give me the following ...
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1answer
18 views

How to handle like meaning sentences when working on text summarization

Suppose we have a text like Today is a very bad day. Very bad day is today. I wont come to play. What kind of technique should I use to summarize similar texts like ...
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21 views

Medical NER for French language

I'm currently exploring the options to extract medical NER specifically for French language. I tried SpaCy's general French NER but it wasn't helpful to the cause (...
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2answers
779 views

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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2answers
1k views

How to create a training set and classify them as positive or negative

I'm trying to create a Sentiment Analysis algorithm for a custom data (government dept specifc data) and not like any other social media data etc. The data exists but I need to categorise the data as ...
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1answer
50 views

word2vec: usefulness of context vectors in classification

I've been working on a NN-based classification system that accepts document vectors as input. I can't really talk about what I'm specifically training the neural net on, so i'm hoping for a more ...
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4answers
130 views

NLP SBert (Bert) for answer comparison STS

I've been researching a good way to automate short answer evaluation. Essentially a teacher gives a test with some questions like: Question: why did columbus sail westward to find asia? Answer: so he ...
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1answer
15 views

Gender identification task on instance or user level?

I'm working on a task which is gender identification. Given a user account (e.g. Twitter account) with its documents (e.g. 100 tweets), the user should be classified as a male or a female. The ...
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1answer
37 views

Is it possible to classify documents of corpus using labels?

I have a corpus of 23000 documents that need to be classified into 5 different categories. I do not have any labeled data available to me, just freeform text documents and labels(yes, one-word labels, ...
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201 views

How do you measure performance for word prediction tasks?

Say I have to predict the next word in a sentence, given the initial few words. Suppose the prefix is "I went to _____". This prefix is common enough that it might appear 10 times in the training ...
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1answer
19 views

What are some of the available methods for handling multi-label classification for longer sequences of text

I am looking to solve a multi-class classification problem with long sequences of text with some rows having 1000's of tokens. Some of the state of the art methods such as BERT have a token limit and ...
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3answers
137 views
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84 views

How to group chat messages by topic?

I am a newbie in this field. Developer since 20 years and more but never done anything (except tutorials) with ML, DL, and NLP. Though I've already read a bunch of articles and tutorials about this ...
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1answer
1k views

What does dimension represent in GloVe pre-trained word vectors?

I'm using GloVe pre-trained word vectors (glove.6b.50d.txt, glove.6b.300d.txt) as word embedding. I have a conceptual question: ...
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1answer
131 views

Why does joint embedding of word and images work?

I often see some papers where the authors do point-wise multiplication of word and image embedding (e.g the image below). Why does this implementation works? I do not understand.
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1answer
41 views

Using BERT for co-reference resolving, what's the loss function?

I'm working my way around using BERT for co-reference resolving. I'm following this highly-cited paper BERT for Coreference Resolution: Baselines and Analysis (https://arxiv.org/pdf/1908.09091.pdf). I ...
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22 views

Is it possible to use unlabeled text articles for summarization when fine tuning BERT?

I know that unlabeled data could be used in pre-training but if I want to do a fine tuning of unlabeled articles for summarization, is it mandatory that the articles are labeled with existing ...
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28 views

Are there any deep models that are better than BERT-CRF in NER task?

Named entity recognition (NER) is task that mark tags of the input text sequence. BERT-CRF is a good NER model. I want to find a better NER model. Or I want to improve the BERT-CRF model. What can I ...
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1answer
35 views

Does building a corpus make sense on a documentation project?

I have zero to experience in data science or machine learning. Because of this I am not able to determine if building a corpus does apply to the problem I am trying to solve. I am trying to build a ...
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3answers
55 views

approach to classify text with natural language processing methods

I have a problem with regards to text classification/categorization. The task is bugging me for days already and as I am pretty new to AI and the field of natural language processing (NLP) I am just ...
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1answer
25 views

how to programmatically introduce grammatical errors in sentences

I've a set of sentences in English language. I'm exploring ways to create a dataset of sentences with grammatical errors programmatically. The following options has been tried out randomly - identify ...
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1answer
106 views

How to implement LSTM using Doc2Vec vectors to get representation?

Hi all. I'm a newbie in ML. I read and found a paper about A Multi-Level Plagiarism Detection System Based on Deep Learning Algorithms and want to implement this model . But I can't find more about ...
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1answer
91 views

Prediction using words which were not in training in a CNN with pre-trained word embeddings

In sentence classification using pre-trained embeddings(fasttext) in a CNN, how does the CNN predict the category of a sentence when the words were not in the training set? I think the trained model ...
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2answers
203 views

Converting paragraphs into sentences

I'm looking for ways to extract sentences from paragraphs of text containing different types of punctuations and all. I used SpaCy's ...

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