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.

90 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
3
votes
2answers
25 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 ...
3
votes
1answer
45 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 ...
3
votes
0answers
87 views

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), ...
2
votes
0answers
16 views

Step extraction from a paragraph

Came across an interesting problem: Given a paragraph describing how to do a process, need to break it down to various steps. Basically, need to determine for each sentence in the paragraph, if this ...
2
votes
0answers
21 views

pros and cons of lexical vs machine learning methods for text mining

I wanted to know what are the pros and cons are of using lexical methods and machine learning methods for classifying texts based topic. I have used a simple method of mining documents related to a ...
2
votes
0answers
35 views

Assigning tags to posts using predefined set of tags

I want to tag the text of a post with a predefined set of tags. A post could have multiple tags such as health, addiction, etc. I want to recommend up to $5$ tags. Total of $60$ tags is present. ...
2
votes
0answers
23 views

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 ...
2
votes
0answers
145 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 ...
2
votes
0answers
31 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: ...
2
votes
0answers
24 views

How do I perform Sentiment Analysis on Tweets in the following pattern:

I have tweets obtained based on matches (football) before the match begins. I have tweets which specify a team will win 3-1 and so on which are easily analyzed using regular expressions. I am facing ...
2
votes
0answers
94 views

Joint embedding of word and image

I often see some papers, in which the authors do the point-wise multiplication of word embedding and the image embedding. As the image shows below, my question is how come the implementation works?? I ...
2
votes
1answer
134 views

How do we pass data to a RNN?

Let's say we have A1, A2, ... , Am different articles in the corpus and each of them has W1, W2, ....., Ww words. We are training a language model on them. Do we: Scheme 1 Take the first batch of ...
2
votes
3answers
116 views

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 ...
1
vote
1answer
16 views

Looking for a causality to effect dataset

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

Automatically categorize parts of a piece of writing

Suppose I had a piece of writing. The document contains aspects like questions, assertions, examples, and explanations. Is it possible to use Natural Language Processing to categorize each sentence of ...
1
vote
1answer
21 views

What is the easiest way to identify a gender for a noun (in a french)?

I am working on an app where in order to process some data, I need to be able to identify the gender for some selected words. My data is in French. The feature I am looking for should be able to tell ...
1
vote
0answers
10 views

Skip-gram trained on The Hobbit: no improvement in the similarity of the word representation

I've trained a simple skipgram NNLM (window size = 5) on The Hobbit. This is the rough pseudocode: ...
1
vote
1answer
29 views

Guidelines to debug REINFORCE-type algorithms?

I implemented a self-critical policy gradient (as described here), for text summarization. However, after training, the results are not as high as expected (actually lower than without RL...). I'm ...
1
vote
0answers
13 views

How can one determine that Word2Vec (CBOW method) embeddings are related to each other?

I read some fascinating stuff about the potential for using the Word2Vec algorithm to speed up the pace of scientific discovery here https://www.researchgate.net/publication/...
1
vote
0answers
9 views

fit transform with mysterious special chracters

I tried to make the bag of words ...
1
vote
1answer
38 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 ...
1
vote
0answers
10 views

Predicting class of email based on its associated parameters

I am solving a challenge where the data represented as above is given. In this challenge I have to associate each email with one of the the 2 criteria (automation, Or SEO). Example if email falls ...
1
vote
0answers
62 views

Integration of NLP and Angular application

I'm doing a small POC in which I've trained my Machine Learning model (Naive Bayes) and is saved in ".pkl" (pickle) format. Now my next task is to develop a web application which asks the user to ...
1
vote
1answer
90 views

Framing Sentences based on keywords

Given a few specific words, which techniques of Natural Language Processing can I use to achieve creating a meaningful sentence from those words? eg. Words: jackets, highest sale, sweaters, lowest ...
1
vote
0answers
168 views

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 ...
1
vote
0answers
37 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 ...
1
vote
0answers
18 views

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 ...
1
vote
0answers
31 views

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 = ...
1
vote
0answers
51 views

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 ...
1
vote
0answers
28 views

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 ...
1
vote
0answers
59 views

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 ...
1
vote
0answers
49 views

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 ...
1
vote
0answers
30 views

How to learn word embedding from a context on the fly?

Consider the fictional word tahiliuk in the sentence “We found a small, fluffy tahiliuk running around our garden.” While hearing a new word used in context, people are remarkably adept at inferring a ...
1
vote
0answers
22 views

TextRank algorithm for Web content

I am looking for an algorithm that would be able to extract meaningful keyphrases from web articles. Each article has more than 2000 words and information is structured using paragraphs, h1, h2 tags ...
1
vote
0answers
191 views

Audio signal signal processing for background noise reduction or removal

I am performing simple audio recognition using tensor-flow to spot key word or hot word detection. The graph takes the microphone input directly and performs "Audio spectrometer --> mfcc's --> and ...
1
vote
0answers
37 views

Using an ontology to recognize named entities in free text

I'm trying to solve a fairly basic problem in NPL efficiently. What tool or software package would you use to identify the words, or group of words that are part of an given ontology within a free ...
1
vote
0answers
19 views

What approach to use to detect violations of media ethics in news?

I've been trying to come up with a solution to detect violations of media ethics in news articles. For example, I need to detect if an article has mentioned the name of a victim of rape. So far, I've ...
1
vote
0answers
28 views

Common deep learning practices in NLP for text classification

Are there any articles about best modern techniques in text classification (not only for English texts, but in general)? In particular, I'm interested: what kind of text preprocessing techniques are ...
1
vote
0answers
31 views

Check If Answer is Correct by Similarity

I am new to data science and machine learning. Let's say that I have a question, and some correct answers for that question (for example, 10 correct answers). Is there a way to get a new answer as ...
1
vote
0answers
11 views

Grouping prefix and term queries

Consider the following context: You have a website that is offering a search function, which produces a list of matching articles. The search has prefix functionality: if you are looking for "...
1
vote
0answers
157 views

Loss function for Hierarchical Multi-label classification

I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels (e.g., a simple MLP branch inside a ...
1
vote
0answers
78 views

How are natural language generation algorithms given a target

I've started learning about NLP and NLG and I'm fascinated! I've been blown away by the things I've seen from NLP; but I have a few questions about NLG. All my questions boil down to this: Given a ...
1
vote
1answer
73 views

Question classification

I have 10 classes and 10-15 questions in each class . Given a new question, I want to find the class to which the question is most similar?
1
vote
2answers
51 views

How should I format input and output for text generation with LSTMs

I'm attempting to generate a response to an input line of text using an LSTM. I've considered various forms of input, including one-hot encoding each character in the line and passing each input line ...
1
vote
0answers
18 views

Machine Learning Text Categorization with Data in multiple Languages

I want to label natural text Dokuments in various different categories (arround 400 different categories) using Neural Networks. I have around 50.000 documents already labeled. The problem is around ...
1
vote
0answers
41 views

Build a relevancy scoring model of articles using NLP

I'm really new to Data Science and text mining. I want to build a relevancy scoring model. Suppose I have a bag of words (guns, military, terrorists). I also have a list of articles. I want to find if ...
0
votes
0answers
7 views

NL2SQL task, if we have enough data, what will the model achieve for hard SQL?

We are afraid that the hard SQL like TABLE JOIN is the limit for industrial application. Addition info: https://yale-lily.github.io/spider Thank you very much.
0
votes
0answers
5 views

How to generate alignments for word-based translation models if number of words are different in both sentences

I am working on implementing IBM Model 1. I have a parallel corpus of some 20,00,000 sentences (English to Dutch). Also, the sentences of the two docs are already aligned. Aim is to translate a Dutch ...
0
votes
0answers
19 views

Why don't we use BCE(Binary Cross Entropy) for language modeling?

I've seen a lot of RNN/Transformer models use cross entropy loss with softmax. but isn't language modeling a multilabel classification task? what happens if we replace cross entropy loss with binary ...
0
votes
0answers
13 views

Combining two structurally similar datasets from different sources

I am working with a text summarization problem, and I am trying to use this architecture [Pointer Generator]. My data set is VERY small (225 samples) compared to the CNN/ Daily Mail dataset this paper ...