Questions tagged [text-classification]

For questions about text classification, the task of assigning predefined categories (or classes) to free-text documents.

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Is there any literature on Span-Level Classification? [closed]

I am currently working on a undergrad thesis project for extracting/scraping data from web pages using machine learning. I need to annotate the data and come up with a sufficient architecture. I’ve ...
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30 views

Distinguishing text with opposite meanings in SVM (False Information Detection)

I am currently working on a Binary Text Classification Model (False Information Detection) using Support Vector Machine and used TF-IDF as text vectorizer in Python. I have already tried training the ...
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Which pre-processing steps are necessary for Deep Learning models to solve a document classification problem?

I have created a data set with 30.000 text documents (each text file is rather small with respect to its length), which are labelled with 0 and 1. Using this data set, I want to train machine learning ...
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Which AI algorithm to use for identifying API for a specific use from a list of APIs?

We have a legacy code solution in C#. We have to change the code so that it fetches internal data via APIs and not via DB calls. E.g. if the current code GETS Payment object from DB, we have to ...
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Find words in a raw text that are similar to a predefined array of words

I need a beginner advice regarding a simple application where I have a very limited set of topics in which i need to identify inside a user's natural language text/sentence. For example, one of the ...
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Get the name of a merchant from records

I have a bunch of bank transaction records from which I want to extract merchants' names. In a few subsets of these records, the structure of the string is the same within the subset with only the ...
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Training and Evaluating BERT and XLNET [closed]

I am thinking about a project and have a few questions before I accept it. Would be grateful I anyone experienced of you could give me some advice. In the project, I have been given a data set with (...
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How to calculate cosine similarity for classification when you have say 10000 samples belonging to two classes have a bunch of samples

Does anyone have experience with using Cosine Similarity for text classification? I see a number of articles on how to find cosine similarity between documents using Doc2Vec, Gensim, etc. I have a ...
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Is it possible to identify multiple queries/intents in an email, check if the reply has addressed all of those queries before sending email?

An email may contain multiple questions related to similar or distinct topics. The person responding the email needs assistance in detecting and informing if all of the questions have been addressed ...
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Is there an AI that can extract proper nouns from free text?

I have some free text (think: blog articles, interview transcripts, chat comments), and would like to explore the text data by analysing the proper nouns it contains. I know of many ways to simply ...
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Advantages of CNN vs. LSTM for sequence data like text or log-files

When do you tend to use CNN rather than LSTM (or the other way round) in classification or generation tasks of sequential data like text or log-data? What are the reasons for the decision and what ...
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Which algorithm can be used for extracting text patterns in tabular data?

I am working with tabular data that is similar to the below: Name Phone Number ISO3 Country Amount Email ... ... Outcome Possible Reason Leona Sunfurry (555)-555-5555 United States 58.96 leo_sun@...
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What approach to use for selecting one of the category according to short category text?

I need some tool to classify articles based on short category text which consists of two or three words separated by '-'. The RSS/XML tag content is for example: Foreign - News Football - Foreign I ...
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Multi class text classification when having only one sample for classes

I have a dataset of texts, each text was identified with an ID number. I would like to do a prediction by finding the best match ID number for upcoming new texts. To use multi text classification, I ...
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How to go about classifying 1000 classes?

I am trying to find research paper with theory(preferably implementation) that is about classifying 1000 (or more) classes. I have heard of an implementation, that initially clustering needs to be ...
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Is using a LSTM, CNN or any other neural network model on top of a Transformer(using hidden states) overkill?

I have recently come across transformers, I am new to Deep Learning. I have seen a paper using CNN and BiLSTM on top of a transformer, the paper uses a transformer(XLM-R) for sentiment analysis in ...
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Bechmark models for Text Classification / Sentiment Classification

I am currently working on a novel application in NLP where I try to classify empathic and non-empathic texts. I would like to compare the performance of my model to some benchmark models. As I am ...
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NLP Bible verse division problem: Whats the best model/method?

I'm working on a project compiling various versions of the Bible into a dataset. For the most part versions separate verses discreetly. In some versions, however, verses are combined. Instead of verse ...
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Can I use one-hot vectors for text classification?

For an upcoming project I'm trying to write a text classifier for the IMDb sentiment analysis dataset. This needs to vectorize words using an embedding layer and then reduce the dimensions of the ...
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2 votes
1 answer
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How do RNN's for sentiment classification deal with different sentence lengths?

I have been doing a course which teaches you about Deep Neural Networks, during one of the exercises I was made to make an RNN for sentiment classification which I did, but I did not understand how an ...
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1 vote
2 answers
191 views

Is it possible that every class has a higher recall than precision for multi-class classification?

I am a student learning machine learning recently, and one thing is keep confusing me, I tried multiple sources and failed to find the related answer. As following table shows (this is from some paper)...
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Text classification of non-equal length texts, should I pad left or right?

Text classification of equal length texts works without padding, but in reality, practically, texts never have the same length. For example, spam filtering on blog article: ...
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NLP Identifying important key words in a corpus

I am intrigued with the idea of Zettelkasten but unsatisfied with the current implementations. It seems to me that a machine learning and NLP approach could be productive by helpfully identifying “...
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My LSTM text classification model seems not learn anything in early epochs

I am trying to use LSTM to do text classification and monitor the training process with tensorboard. But it seems that this model doesn't learn anything in early epochs. Is it normal for LSTM networks?...
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Applications of polar decomposition in Machine Learning

Assume there exists a new and very efficient algorithm for calculating the polar decomposition of a matrix $A=UP$, where $U$ is a unitary matrix and $P$ is a positive-semidefinite Hermitian matrix. ...
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How many spectrogram frames per input character does text-to-speech (TTS) system Tacotron-2 generate?

I've been reading on Tacotron-2, a text-to-speech system, that generates speech just-like humans (indistinguishable from humans) using the GitHub https://github.com/Rayhane-mamah/Tacotron-2. I'm very ...
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Creating Text Features using word2vec

My task is to classify some texts. I have used word2vec to represent text words and I pass them to an LSTM as input. Taking into account that texts do not contain the same number of words, is it a ...
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Top Frequent occurrence word effect in Model Efficiency?

Assume that I have a Dataframe with the text column. Problem: Classification / Prediction ...
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1 answer
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Can artificial intelligence classify textual records?

I am a records manager and I am being asked if I recommend Office 365. I'm having a hard time making a recommendation because I am missing an essential piece of information: can Office 365 replace ...
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Are bayesian neural networks suited for text (or document) classification?

I've tried to do my research on Bayesian neural networks online, but I find most of them are used for image classification. This is probably due to the nature of Bayesian neural networks, which may be ...
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1 answer
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Is it possible to derive meaning from text by providing multiple ways of saying the same thing to a neural network?

Let's say I feed a neural network with multiple string sentences that mean roughly the same thing but are formulated differently. Will the neural network be able to derive patterns of meaning in the ...
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Language Learning feedback with AI

Is there a program under development that uses AI technology, like Siri, to "hold hands" so to speak with a language learner and coach them on accent, colloqiual expressions, or to let them guide the ...
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1 answer
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When is it time to switch to deep neural networks from simple networks in text classification problems?

I did an out of domain detection task (as a binary classification problem) and tried LR and Naive Bayes and BERT but the deep neural network didn't perform better than LR and NB. For the LR I just ...
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1 vote
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29 views

Text detection on English and Chinese language

https://arxiv.org/abs/1910.07954 In this paper, we have a convolutional character neural network where we have object detection by taking a character as a basic unit. First, we do character detection ...
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2 votes
1 answer
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How does the weight update formula for logistic regression work?

I am trying to use Logistic Regression to make a spam filter, but I am having trouble understanding the weight update part. I have processed my email dataset, and I have an attribute vector of the top ...
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4 votes
2 answers
106 views

Does summing up word vectors destroy their meaning?

For example, I have a paragraph that I want to classify in a binary manner. But because the inputs have to have a fixed length, I need to ensure that every paragraph is represented by a uniform ...
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2 votes
1 answer
34 views

How can a system recognize if two strings have the same or similar meaning?

How can a system recognize if two strings have the same or similar meaning? For example, consider the following two strings Wikipedia provides good information. Wikipedia is a good source of ...
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4 votes
2 answers
86 views

Is there any classifier that works best in general for NLP based projects?

I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a ...
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3 votes
2 answers
404 views

How to use LSTM to generate a paragraph

A LSTM model can be trained to generate text sequences by feeding the first word. After feeding the first word, the model will generate a sequence of words (a sentence). Feed the first word to get the ...
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1 vote
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What is the most accurate pretrained sentiment analysis model by 2019?

I've been using OpenAI's 2017 Sentiment Neuron implementation (https://github.com/openai/generating-reviews-discovering-sentiment) for a while, because it was easy to set up and was the most accurate ...
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90 views

How to train LSTM score prediction with very little data? (Bounty to be added)

I am trying to make a text score prediction network, and my dataset have 500 samples only. I know there is a public dataset called the ASAP Dataset. I have tested my model ...
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2 votes
1 answer
244 views

Is a dataset of roughly 700 sentences of an average length of 15 words enough for text classification?

I'm building a customer assistant chatbot in Python. So, I am modelling this problem as a text classification task. I have available more or less 7 hundred sentences of an average length of 15 words (...
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8 votes
1 answer
179 views

Why are documents kept separated when training a text classifier?

Most of the literature considers text classification as the classification of documents. When using the bag-of-words and Bayesian classification, they usually use the statistic TF-IDF, where TF ...
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