2021-04-13 17:02:00, Jared Council, WSJ

Content Categorization
/Computers & Electronics
/Science/Computer Science
/Business & Industrial

Word Count:
222

Words/Sentence:
20

Reading Time:
2.22 min

Reading Quality:
Advanced

Readability:
16th or higher

Media Sentiment
Proprietary sentiment analysis on both the headline and body text of the article. Sentiment scores range from -1 (very negative sentiment) to 1 (very positive sentiment).
RCS Analysis
Relative scoring for Risk, Crisis, and Security language within the article.
Risk Score
Scoring based on the composite risk, security and crisis language within an article compared to a baseline of historic analysis across thousands of diverse articles.
PESTEL Scope
Analysis of article orientation across the PESTEL macro-environmental analysis framework. Learn more about PESTEL.
Entity Word Cloud
Key people, places, organizations and events referenced in the article, weighted by frequency and colored based on contextual sentiment.
Auto Summary
Condensing key features of the article based on salience analysis. Helpful for “gisting” the article in a time crunch.

In its early days, the process of getting computers to analyze and understand language involved hard-coded software rules and expert systems, according to Dr. Picheny, who's been working in the field since 1979.

Research firm Gartner predicts that by 2025, 50% of knowledge workers will use an NLP-powered virtual assistant daily, up from 5% in 2020.

Here's how natural language processing works.

Its pioneers include linguist Noam Chomsky and computer scientist John McCarthy, according to Michael Picheny, a research professor at New York University's Courant Institute Computer Science Department and Center for Data Science.

will bolster its strength in natural language processing, artificial intelligence that can interpret and respond to human language.

It powers Apple Inc.'s Siri and Amazon.com Inc.'s Alexa and automated call-center attendants.

Keywords
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