3 Ways to Analyze the State of the Union with Text Analytics
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3 Ways to Analyze the State of the Union with Text Analytics
Text Analytics

3 Ways to Analyze the State of the Union with Text Analytics

To most people, analyzing last week’s State of the Union address, is something politicians and talking heads do....

Semantria and Diffbot: A Partnership That Makes a Big Diff
Announcements

Semantria and Diffbot: A Partnership That Makes a Big Diff

Big News! Semantria and Diffbot, a San Francisco-based start-up that specializes in intelligent web page...

Using Semantria to Analyze Reddit Comments
Natural Language Processing

Using Semantria to Analyze Reddit Comments

We took our NLP engine and focused it on Reddit's five year goals. The insights are...

Salience 5.2 Walkthrough: Entity Extraction
Named Entity Extraction

Salience 5.2 Walkthrough: Entity Extraction

One of Salience’s many text analysis capabilities is Named Entity Extraction. Named entities are companies, people,...

Salience 5.2 Walkthrough: Themes
Topic Extraction

Salience 5.2 Walkthrough: Themes

Curious about how our text analytics API sizes up? We’ve written a series of articles to demonstrate some of the...

What is a Matrix? A Quick Guide to Matrices
Machine Learning

What is a Matrix? A Quick Guide to Matrices

What is a matrix, and what is it used for? This short article will attempt to de-mystify this complex mathematical...

Classification: Queries vs. Models
Categorization

Classification: Queries vs. Models

Classification is a few value proposition for text analytics – it allows users to quickly drill into articles of...

Salience and Homonyms
Language

Salience and Homonyms

Language is confusing, imprecise, and often times illogical. The fact that “Buffalo buffalo Buffalo buffalo buffalo...

Tagging, Taxonomies, Categorization with Salience
Categorization

Tagging, Taxonomies, Categorization with Salience

The world is your oyster… And if your world is data, Salience is your pearl. One of the things that makes this...

Sentiment and Litotes: How Salience Deals with Double Negatives
Language

Sentiment and Litotes: How Salience Deals with Double Negatives

The double negative is not an uncommon rhetorical device. (See what I did there?) Using two negatives to indicate a...

The Avengers:  Most Popular Superhero?
Lexalytics

The Avengers: Most Popular Superhero?

The Avengers occupy a big seat in the ever expanding Marvel Cinematic Universe. So, which super hero is the fan...

Salience 4.3: Opinion Mining
Sentiment Analysis

Salience 4.3: Opinion Mining

One of the two major new features in Salience 4.3 (releasing around June 30th) is “opinion mining”. Opinion...