Neuro Symbolic AI for Sentiment Analysis - Michael Malak

2,541 views · Published 8 June 2017 · 24:50 · Indexed 3 October 2026

Channel: Databricks · 2017 · Science & Technology

Watch on YouTube

"Learn to supercharge sentiment analysis with neural networks and graphs. Neural networks are great at automated black-box pattern recognition, graphs at encoding and human-readable logic. Neuro-symbolic computing promises to leverage the best of both.
 
In this session, you will see how to combine an off-the-shelf neuro-symbolic algorithm, word2vec, with a neural network (Convolutional Neural Network, or CNN) and a symbolic graph, both added to the neuro-symbolic pipeline. The result is an all-Apache Spark text sentiment analysis more accurate than either neural alone or symbolic alone.
 
Although the presentation will be highly technical, high-level concepts and data flows will be highlighted and visually explained for the more casual attendees. Technologies used include MLlib, GraphX, and mCNN (from spark-packages.org) will be highlighted and visually explained for the more casual attendees.

Technologies used: MLlib, GraphX, and mCNN (from spark-packages.org)

Session hashtag: #SFr12"

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