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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 ...

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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 ...
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What is the correct way to calculate the entropy of a language model on a data-set of sentences?

I want to fit the parameters of my language model by minimizing the entropy/ maximizing likelihood of my language model on my data-set. However, I am uncertain as how I should go about doing this. ...
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Comment Classifier

I have a problem where I'm trying to sort comments on cases by their types People type different comments in response to questions customers ask. Mostly though the comment will either be a comment ...
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52 views

Classification of Conversations in Text

I am trying to pick a technique for classifying conversational text. I am concerned about treating the problem at a level of fidelity of each individual message because people often say things like, "...
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25 views

Intiative detection problem

I currently try to wrap my head around a problem of detecting an initiative in a company report document. The following are the types of initiatives a company can report: health, no_poverty, ...
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1answer
20 views

Confidence Intervals for Multi-Categorical Votes

I have an ngram-based language model that produces a long tag list for a given sentence. For example, the just-previous sentence, broken into bigrams, and run through the model might produce something ...
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1answer
16 views

best activation function for ensemble?

i have created some logistic regression model (different preprocessing) with softmax function. and i mix all model with an ensemble with a hierarchical method. so the output of all model (base) will ...
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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 ...
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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 ...
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Recommending top answerers for a Question on Quora/Stackexchange sites

I want to make a tool that will tell me who can potentially answer a question on Quora or StackExchange. The tool will take input the text of a question, and output a sorted list of users who can ...
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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 ...
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1answer
19 views

word/sentence alignment for English document

I have a English document, which is preprocessed into two versions. I want to align words or sentences from these two versions of document. A simple example is as below: ...
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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 ...
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Difference between IOB and IOB2 format?

I have to tag a dataset for NER. I came across conll2002/esp. What I understand so far, in IOB2 format if I want to tag '...
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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 ...
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1answer
26 views

Classifying whether a comment or review is a complaint or appreciation of product and extracting the Topic?

I need to classify whether a given review or comment is a complaint or appreciation. This is planned to be used in multiple places, product review pages of own site as well as facebook and twitter. ...
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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 "...
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1answer
19 views

how to encode labels for relationship extraction

I am trying to extract relationship from text. So, lets take the following text "He went to movie. but, they went to school" So, here the relationship's are "He and Movie", "they and school". How ...
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13 views

NLP research: Emotive conjugation

Is there any formal NLP research into emotive conjugation (aka Russel's conjugation)? Here are some examples of emotive conjugation by Bertrand Russell that are shown on the Wikipedia page: I am ...
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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 ...
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20 views

Unsupervised answering for a predefined set of questions

I am working on a project to read up a text segment and find answers to a specific set of questions, in order to do some information extraction. I have a set of text corpus (each of about 3000 words),...
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How to extract event from news article and merge similar event together

TL;DR Is there a way to extract events from news and cluster similar news event together? I am following the ACE methodology currently, is that a viable way? Longer version: I am currently working ...
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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 ...
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26 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), ...
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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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Extract/detect IDs (like flight booking ids) from text

I'm looking to extract ids from the body of an email. The ids are similar to flight booking IDs. For example, in an email, I would like to obtain the booking reference (something like MNFF3RGC or MNF-...
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Expanding entity extraction to certain types of named-noun phrases (Bi-grams or tri-grams)

I have a corpus of articles from business publications. I'm interesting in extraction information relating to specific types of technologies and processes, as well as just interesting phrases. ...
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1answer
36 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?
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1answer
16 views

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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1answer
26 views

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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47 views

Data scraping & NLP?

I'm scraping data from Bing search results for (non-commercial purposes, of course) on Python using BeautifulSoup. I've entered an Indian dessert name, called 'rasmalai' as the word that I am focusing ...
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25 views

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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54 views

Case-Sensitive Word Embeddings for French

Are there any pre-trained case-sensitive word embeddings for French? The only word embeddings for French I have found is FastText and it is not case sensitive. I am currently working on problems ...
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1answer
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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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95 views

transfer learning with sentiment analysis?

The question is how good and what are some things to keep in mind when sentiment analysis models are tested on different datasets than they are trained on. Say the task is to perform sentiment ...
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2answers
27 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 ...
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1answer
92 views

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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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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2answers
2k views

Natural Language to SQL query

I have been working on developing a system "Converting Natural Language to SQL Query". I have read the answer from the similar questions, but was not able to get the information what I was looking ...
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1answer
98 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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1answer
51 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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28 views

Recommended Modelling Technique for Influencer Marketing Scenario

I have an approximately 90,000 row dataset that has information of social media profiles which has columns for biography, follower count, language spoken, name, username and the label (to identify ...
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16 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 ...
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31 views

Question about CBOW prediction?

I have a question about CBOW prediction. Suppose my job is to use 3 surrounding words w(t-3), w(t-2), w(t-1)as input to predict one target word w(t). Once the model is trained and I want to predict a ...
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2answers
44 views

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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1answer
44 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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How to score documents in a hierarchy?

I am trying to learn the ways of data science applied to natural language. I extracted categories from wikipedia (also see this question) with a depth of 3. That is I have a hierarchy that looks like ...
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1answer
35 views

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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2answers
139 views

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 ...