Showing posts with label natural language processing. Show all posts
Showing posts with label natural language processing. Show all posts

Deep Learning Sentiment Analysis for Movie Reviews using Neo4j

Monday, September 15, 2014

While the title of this article references Deep Learning, it's important to note that the process described below is more of a deep learning metaphor into a graph-based machine learning algorithm. No neural networks are used.

Sentiment analysis uses natural language processing to extract features of a text that relate to subjective information found in source materials.

Movie Review Sentiment Analysis

A movie review website allows users to submit reviews describing what they either liked or disliked about a particular movie. Being able to mine these reviews and generate valuable meta data that describes its content provides an opportunity to understand the general sentiment around that movie in a democratized way. That’s a pretty cool thing if you think about it. Using machine learning we can democratize subjectivity about anything in the world. We can make an objective analysis of subjective content, giving us the ability to better understand trends around products and services that we can use to make better decisions as consumers.

Using a Graph Database for Deep Learning Text Classification

Tuesday, August 26, 2014

Graphify is a Neo4j unmanaged extension that provides plug and play natural language text classification.

Graphify gives you a mechanism to train natural language parsing models that extract features of a text using deep learning. When training a model to recognize the meaning of a text, you can send an article of text with a provided set of labels that describe the nature of the text. Over time the natural language parsing model in Neo4j will grow to identify those features that optimally disambiguate a text to a set of classes.

Feature Hierarchy