One of the most important and most-used functions in text analytics and NLP is sentiment analysis — the process of determining whether a word, phrase, or document is positive, negative, or neutral. The first step […]
The Blog.
Dude, Where’s My Neural Net? An Informal and Slightly Personal History
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40 m
It pretty much started here: McCulloch and Pitts wrote a paper [1] describing an idealized neuron as a threshold logic device and showed that an arrangement of such devices could express any propositional logic formula. […]
The 7 Basic Functions of Text Analytics & Text Mining
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7 m
From Tokenization to PoS Tagging and beyond, this high-level overview explains the basic functions of text analytics and natural language processing.
Best Text Analytics Solutions: The Ultimate Guide
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15 m
Discover how the top 6 text analytics vendors differ from one another and learn about which platform suits which use case. This comprehensive text analytics guide serves as the who’s who and the what’s what in natural language processing.
Machine Learning Micromodels: More Data is Not Always Better
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6 m
Machine learning micromodels reduce the challenges of sourcing and annotating data while delivering better precision and accuracy than macromodels.
The Ultimate NLP Tuning FAQ: Sentiment, Topics and More
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11 m
Lexalytics Support Engineer Sarah Williams answers our users’ most frequently-asked questions about how to tune Lexalytics’ natural language processing.
Natural Language Processing in 5 Minutes
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4 m
What is natural language processing? And what does it mean for you, me and your drunk friend? Seth Redmore explains the fundamental concepts of NLP in 5 minutes or fewer.
Using Semantria to Analyze Reddit Comments
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3 m
We took our NLP engine and focused it on Reddit’s five year goals. The insights are fascinating.
What is a Matrix? A Quick Guide to Matrices
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3 m
What is a matrix, and what is it used for? This short article will attempt to de-mystify this complex mathematical concept for natural language processing.