NLP Town Blog

Comparing Sentence Similarity Methods

Word embeddings have become widespread in Natural Language Processing. They allow us to easilycompute the semantic similarity between two words, or to find the words most similar to a target word.However, often we're more interested in the similarity between two sentences or short texts.In this b...

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Why computers don’t yet read better than us

Artificial Intelligence is on a roll these days. It feels like the media report a new breakthrough every day. In 2017, computer and board games were at the center of public attention, but this year things look different. In the early days of 2018, both Microsoft and Alibaba claimed to have develo...

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Named Entity Recognition and the Road to Deep Learning

Not so very long ago, Natural Language Processing looked very different. In sequence labelling tasks such as Named Entity Recognition, Conditional Random Fields were the go-to model. The main challenge for NLPengineers consisted in finding good features that captured their data well. Today, deep ...

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Perplexed by Game of Thrones. A Song of N-Grams and Language Models

N-grams have long been part of the arsenal of every NLPer. These fixed-length word sequences are not only ubiquitous as features in NLP tasks such as text classification, but also formed the basis of the language models underlying machine translation and speech recognition. However, with the adve...

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Anything2Vec, or How Word2Vec Conquered NLP

Word embeddings are one of the main drivers behind the success of deep learning in Natural Language Processing. Even technical people outside of NLP have often heard of word2vec and its uncanny ability to model the semantic relationship between a noun and its gender or the names of countries and ...

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Understanding Deep Learning Models in NLP

Deep learning methods have taken Artificial Intelligence by storm. As their dominance grows, one inconvenient truth is slowly emerging: we don’t actually understand these complex models very well. Our lack of understanding leads to some uncomfortable questions.Do we want to travel in self-driving...

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DIY methods for sentiment analysis

In my previous blog post, I explored the wide variety of off-the-shelf solutions that are available for sentiment analysis. The variation in accuracy, both within and between models, led to the question whether you’re better off building your own model instead of trusting a pre-trained solution. ...

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Off-the-shelf methods for sentiment analysis

Sentiment analysis is one of the most popular applications of Natural Language Processing. Many companies run software that automatically classifies a text as positive, negative or neutral to monitor how their products are received online. Other people use sentiment analysis to conduct political ...

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Text Classification Made Simple  

When you need to tackle an NLP task — say, text classification or sentiment analysis — the sheer number of available software options can be overwhelming. Task-specific packages, generic libraries and cloud APIs all claim to offer the best solution to your problem, and it can be hard ...

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NLP in the Cloud: Measuring the Quality of NLP APIs

Natural Language Processing seems to have become somewhat of a commodity in recent years. More than a few companies have sprung up that offer basic NLP capabilities through a cloud API. If you’d like to know whether a text carries a positive or negative message, or what people or companies it men...

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NLP People: the 2016 NLP job market analysis

When the University of Leuven asked me to give a guest lecture in their Master of Artificial Intelligence earlier this year, one thing I set out to do was to give students an idea of the opportunities in the NLP job market. I contacted Alex and Maxim from NLP People, and they were so kind to give...

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Generating Genre Fiction with Deep Learning

These days Deep Learning is everywhere. Neural networks are used for just about every task in Natural Language Processing — from named entity recognition to sentiment analysis and machine translation. A few months ago, Andrej Karpathy, PhD student at Stanford University, released a small s...

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