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.

Filter by
Sorted by
Tagged with
1 vote
1 answer
24 views

Matching 2 keywords list using NLP

I have two lists and I want to identify which elements are common (same or similar in meaning or context) in the list. Which NLP algorithm we should use. ...
user avatar
0 votes
0 answers
14 views

Can word2vec's neural network itself, and not the embedding weights, be used for word prediction?

Given the shallow neural network that was used to train e.g.: a skip-gram model, my question is: Can we actually use this network to predict probable context words? What is the output of this network? ...
user avatar
0 votes
0 answers
68 views

Combine different datasets for ensemble model in Keras

Dataset1 is a list of comments with 30 classes (~130k records) from Source 1. Dataset2 is list of comments with 2 classes (~50k records) from source 2. Since ML model wasn't giving good results just ...
user avatar
  • 1
0 votes
1 answer
21 views

what kind of technique to use for below task?

I'm working on a project to recognize confidential info like social security number, name, driver license number, financial details(like credit card number, account details etc), address, certain ...
user avatar
1 vote
0 answers
38 views

BERT each Word Embedding in Keras

How to use BERT to extract the embeddings of every word in a sentence. Suppose I pass my corpus of sentences with different lengths to a BERT model , I want to be able to extract the embeddings of ...
user avatar
  • 13
0 votes
0 answers
306 views

Pytorch build_vocab_from_iterator giving vocabulary with very few words

I am trying to build a translation model in pytorch. Following this post on pytorch I downloaded the multi30k dataset and spacy models for English and German. ...
user avatar
  • 3
0 votes
0 answers
51 views

How Transformer Decoders Use Mask to Prevent Ground Truth Leakage During Training process

After reading the original paper and many articles and blogs, I have a general understanding of Transformer. I still have some doubts about the Mask, I know it is to prevent the subsequent positions ...
user avatar
  • 1
0 votes
0 answers
8 views

Extracting data from human-to-human chat

I have a problem to solve and was hoping you could advise/point me in the right direction. The problem is: people returning products from my niche store talk to employees via a built-in chat. They ...
user avatar
0 votes
0 answers
56 views

How to choose similarity measurement between sentences and paragraphs

Problems 1. How to find appropriate measurement method There are several ways to measure sentence similarities, but I have no idea how to find appropriate method among them for my data (sentences). ...
user avatar
  • 37
0 votes
1 answer
127 views

Sequence Embedding using embedding layer: how does the network architecture influence it? [closed]

I want to obtain a dense vector representation of protein sequences so that I can meaningfully represent them in an embedding space. We can consider them as sequences of letters, in particular there ...
user avatar
1 vote
1 answer
77 views

Understanding how Long Short-Term Memory works in classification of sequences of symbols

I want to use a LSTM neural network to classify sequences of protein according to the host species. For example, I have these sequences of letters (toy example, just to understand): ...
user avatar
0 votes
1 answer
46 views

Pretrained German BERT

I'm looking for a (well) pretrained BERT Model in German to be adapted in a Keras/TF framework. Ideally with a minimal example on how to fine-tune the model on specific tasks, i.e. text classification!...
user avatar
  • 6,872
0 votes
0 answers
25 views

Grouping tweets and newspaper articles by topic

i want to implement a software that groups twitter posts to other twitter posts or to newspaper articles with similar topics. Let's say for example someone tweets about a soccer game and at the same ...
user avatar
  • 1
0 votes
0 answers
10 views

Can linguistic relationships be derived from word-embedding models?

Transformations in Embedding space One fascinating property of word-embedding models like GloVe and word2vec is that linguistic transformations can be described as bi-directional vectors mapping ...
user avatar
0 votes
0 answers
16 views

How was the vocab built using WordPiece for the paper exBERT?

In the paper exBERT: Extending Pre-trained Models with Domain-specific Vocabulary Under Constrained Training Resources the authors point out that: First, we derive an extension vocabulary from the ...
user avatar
  • 313
0 votes
1 answer
156 views

What are the differences between bert embedding and flair embedding

I read about BERT embedding model and FLAIR embedding model, and I'm not sure I can tell what are the differences between them ? ...
user avatar
1 vote
0 answers
35 views

Which will be best deep learning model for topic classification using NLP [closed]

I have a dataset consisting of two columns [Text, topic_labels]. Topic_labels are of 6 categories for ex: [plants,animals,birds,insects etc] I would like to build deep learning-based models in order ...
user avatar
  • 11
1 vote
0 answers
14 views

Consistency between multiple word predictions in a single NLP sentence

Considering a model which predicts multiple missing words in a sentence: The ___ is preparing the ___ in the ___ There is no pre-existing context in this masked ...
user avatar
  • 165
0 votes
1 answer
20 views

Clustering tables (with similar schema) together

I have been working on a problem but unable to make substantial progress so wanting some insights/advice. I have a large set of tables (CSV files) having only column names. (Column values are not ...
user avatar
0 votes
0 answers
11 views

Why does a Classic Neural Network perform better than RNN in text classification?

Im trying to do text classification for the first time without using any tutorial and after a week of trying LSTMs and changing parameters I only got 60% accuracy but in the moment I used a Classic ...
user avatar
0 votes
1 answer
25 views

How to select a proper vectorization method in NLP?

Suppose we have a text classification problem. As we all know we have to convert the text data into vectors so as to train the model. So there are a couple of vectorization methods such as count ...
user avatar
  • 177
0 votes
1 answer
34 views

Sequence-to-Sequence Transformer for Neural machine translation

I am using the tutorial in Keras documentation here. I am new to deep learning. On a different dataset Menyo-20k dataset, of about 10071 total pairs, 7051 training ...
user avatar
  • 17
0 votes
0 answers
7 views

Dataset with Multiple Choice Questions for fine tuning

I hope it's allowed to ask here, but I am looking for a dataset (the format is not that important) that is similar to SQuAD, but it also contains false answers to the questions. I wanna use it to fine ...
user avatar
0 votes
0 answers
21 views

NLP: Finding questions or information sought in a paragraph

I am a newbie in Natural Language Processing. I recently explored IBM Natural Language Understanding (NLU) based on the tutorials given on their website. But still I am unable to proceed toward my ...
user avatar
  • 101
1 vote
2 answers
66 views

NLP Interview Coding Task

Please comment on the following NLP Interview Coding Task that I have prepared for the candidates on Data Science NLP position that I am looking for. The goal is to check candidate understanding of ...
user avatar
  • 263
0 votes
1 answer
9 views

Should I create single feature for each specific word which i find in text or one for all them?

I am doing feature engineering right now for my classification task. In my dataframe I have a column with text messages. I decided to create a binary feature which depends on whether or not in this ...
user avatar
  • 113
0 votes
0 answers
24 views

Reversing a dependency tree into the original sentence

I'm wondering if it is possible to convert a dependency parser such as ...
user avatar
0 votes
0 answers
50 views

Fine tune t5-small for text summarization

I am trying to fine tune t5-small for text summarization, and I have the following graph loss per batch: and learning rate per batch: Do you think loss graph is normal (regarding this use case) or ...
user avatar
0 votes
2 answers
97 views

Why does averaging word embedding vectors (exctracted from the NN embedding layer) work to represent sentences?

I'm puzzling to understand why the method of averaging word embeddings works in order to obtain sentence embedding, in particular considering the exercize of this post How to obtain vector ...
user avatar
0 votes
0 answers
21 views

Unsupervised clustering for Text labelling

I have millions semi structured text descriptions of a job requirement. Which needs to be labelled, such as the number of hours, years of experience required, shifts, certifications, licensure etc., ...
user avatar
1 vote
1 answer
20 views

How could I improve my classifier of text data?

I have a dataset with three columns "message", "city" and "has_info". Here is a sample of it: ...
user avatar
  • 113
0 votes
0 answers
20 views

Regarding pos tagging

I working on a dataset, I did the pos_tagging using nltk. Now I want to know which sequence of grammar is most common in my rows, then I want to define a chunk grammar based on a common grammar ...
user avatar
0 votes
0 answers
25 views

Where to start with ChatBots?

I want to start my journey into ChatBots and how I can create them. I have read some articles regarding the type of chatbots. Basically there are 2 types of chatbots, one is a rule based and the other ...
user avatar
  • 1,231
1 vote
0 answers
18 views

Which ML to use for search suggestion?

Problem: I want to create a program to organize text information and fast access to relevant documents. I would like to train a ML model to analyse the current situation and to suggest the next ...
user avatar
0 votes
1 answer
23 views

Get sentence embeddings of transformer-based models

I want to get sentence embeddings of transformer-based models (Bert, Roberta, Albert, Electra...). I plan on doing mean pooling on the hidden states of the second last layer just as what bert-as-...
user avatar
  • 145
1 vote
0 answers
15 views

What can be the approaches to merge (ensemble) a NON-Probabilistic model with RandomForest?

I have a RF for Text classification and it gives me accuracy. Almost same metric is given by another model built using ...
user avatar
  • 313
1 vote
1 answer
25 views

does ValueError: 'rat' is not in list means not exist in tokenizer

Does this error means that the word doesn't exist in the tokenizer return sent.split(" ").index(word) ValueError: 'rat' is not in list the code sequences ...
user avatar
0 votes
0 answers
65 views

How to get fine-grained sentiment score from text data under unsupervised learning?

In my experience I have only used LSTM models to do sentiment classification tasks on text data under supervised learning. For example, the imdb dataset from keras which is a binary classification ...
user avatar
0 votes
1 answer
177 views

How can i get the vector of word using BERT?

I need to get word-vectors using BERT and got this function that i think it should be the one i need ...
user avatar
2 votes
1 answer
180 views

Custom Named-Entity Recognition (NER) in product titles using deep learning

I am new to machine learning and Natural Language Processing (NLP). I am trying to identify which brand, product name, dimension, color, ... a product has from its product title. That is, from 'Sony ...
user avatar
0 votes
1 answer
354 views

Difference between Doc2Vec and BERT

I am trying to understand the difference between Doc2Vec and BERT. I do understand that doc2vec uses a paragraph ID which also serves as a paragraph vector. I am not sure though if that paragraph ID ...
user avatar
  • 23
0 votes
0 answers
54 views

NLP: Checking that answers to a question are correct

Question answering is a common topic within NLP, but my problem is a little different: rather than answering a question, I have a question, an (open-ended) answer, and what I want to check is if that ...
user avatar
  • 101
0 votes
0 answers
12 views

NLP with what to replace names in sentences?

My task is named entity-sentiment analysis, and I see if I change the name in the sentence then sentiment can change. Are there any methods to avoid this problem? I think to replace these words with ...
user avatar
0 votes
0 answers
8 views

Natural Language gender classification task with very small training set

The task involving determining the gender of the creator of a Reddit post. Given a post and its title, I need a model to output a probability vector $[p_{male},p_{female}]$. The difficulty here is ...
user avatar
0 votes
2 answers
89 views

How to categorise customer complaint using NLP

I have a dataset of community complaints and I would like to build a NLP model on those descriptions and tag a category (can be referred for an inspection or Not ie "Not referred) to each of them....
user avatar
  • 103
0 votes
0 answers
15 views

Whether the goal of a conversation has been reached or not

I have the call transcripts of chats between a customer and an agent. How do I predict whether the main issue has been resolved by the agent or not? These are call transcripts from call centers. So we ...
user avatar
0 votes
0 answers
14 views

Best methods to choose between different searching models?

My question here is in regards to best practices and current methods for selecting search models on the fly based on a users query. Lets say I have four searching models, each optimized for their ...
user avatar
  • 113
1 vote
1 answer
24 views

What are the best methods to reduce the bag of words dimensionality?

I have a small text dataset with 600 comments. My task is a binary classification one. In order to train my model, I transformed the comments into a bag of words using sklearn CountVectorizer. The ...
user avatar
2 votes
0 answers
18 views

Classification Texte with naive bayes complement

Currently I am on a text classification project, the goal is to classify a set of CVs according to 13 classes. I use the bayes algorithm (ComplementNB), in my tests it is the model that gives the ...
user avatar
2 votes
0 answers
18 views

Comparing the cosine similarities of the same word representations, from two separate models (vector spaces)

I am comparing the cosine similarities of word representations derived from a BERT model and also from a static Word2Vec model. I understand that the vector spaces of the two models are inherently ...
user avatar

1 2 3
4
5
47