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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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 ...
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How to select features for clustering to detect the number of different unique products in a search result?

I am trying to use clustering to determine the number of products in a search of products. So far I am using kmeans clustering. I have run into a problem where I cannot determine good features to use. ...
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How to find impactful words affecting classification?

So I know there are many methods to classify sentences into types. Like in sentiment analysis (positive, negative, neutral), spam emails (spam, not spam), etc. The thing I want to ask is how would I ...
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Tools and Techniques for Analyzing German Automotive Discussion Forum Posts [closed]

I work for a German online disussion forum around all things automotive, a bit like a “StackOverflow for cars”, if you will. We would like to train a model using TensorFlow with our high quality ...
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Predicting a new document [closed]

I have a document, (purchase agreement) of approx. 100 pages. This document is sent from buyer to seller several times, and each time there is a negotiation. Negotiation could be anything. For eg. ...
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Fine-tuning NLP models

In computer vision, if we don't have a large training set, a common method is to start with a pre-trained model for some related task (e.g., ImageNet) and fine-tune that model to solve our problem. ...
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Is it valid to include your validation data in your vocabulary for NLP?

At the moment, I am following best practices and creating a "bag of words" vector with a vocabulary from the training data. My cross validation (and test) datasets are transformed using this model, ...
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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 ...
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Training an AI to play Starcraft 2 with superhuman level of performance?

I'm interested in working on challenging AI problems, and after reading this article (https://deepmind.com/blog/deepmind-and-blizzard-open-starcraft-ii-ai-research-environment/) by DeepMind and ...
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1answer
73 views

Machine Learning and Natural Language Processing : Project Initiation

I am in the research phase of a long project and am willing to get some useful feedback from your side about the most appropriate project path to take. Current situation: A large team of so called ...
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what machine/deep learning/ nlp techniques are used to classify a given words as name, mobile number, address, email, state, county, city etc

I am trying to generate an intelligent model which can scan a set of words or strings and classify them as names, mobile numbers, addresses, cities, states, countries and other entities using machine ...
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302 views

How to combine sparse text features with user smile for sentiment classification? [closed]

I am trying to perform sentiment classification task where I have some text and some information about whether the user smiled or not. Now when I use count-vectorizer to convert my text to feature ...
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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 ...
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78 views

What distance should I use for edges weights in textrank algorithm

I found this python implementation on github with 400+ stars which use levenshtein distance between each nodes. But original paper (page 4) said: Next, all lexical units that pass the syntactic ...
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Should I remove features that occur very rarely to build a model?

I am trying ML techniques in language processing. I have got 3000 short texts and I extract features(words and phrases) from all of them and build a vocabulary. I end up with 6000 od features and most ...
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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
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Why are Chunking and IOB tags necessary?

I've just come across chunking and I can't get my head around why is it necessary? I know that it is used for 'named entity recognition'. I have few questions: Why and how is Chunking helpful? Plus ...
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1answer
649 views

Words as features of a neural networks

I'm new in Machine learning and I'm working on a problem related to text. I know that in ML we can use features as numerical values as input to neural network, but I don't know how to use features as ...
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Sentiment Analysis [closed]

I am currently doing a project in python. This project is Aspect based sentiment analysis. I don't know how to prepare training file for that
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GloVe vector representation homomorphism question

In the paper GloVe: Global Vectors for Word Representation, there is this part (bottom of third page) I don't understand: I understand what groups and homomorphisms are. What I don't understand is ...