Using NLP + Neo4j for a Social Media Recommendation Engine
Blog post from Neo4j
The GraphAware Natural Language Processing (NLP) plugin, developed as part of the GraphAware Enterprise Reco plugin for Neo4j, is used to deliver high-quality recommendations to end users by combining content-based and ontology-based cosine similarities with a collaborative filtering approach. The plugin models documents using three dimensions: Content, Tag, and User, providing different views of the document's meaning. It uses a combined approach to compute document similarity, creating three vectors for each document based on its internal content, tags, and user interactions. These vectors are then used to calculate a combined similarity score, which represents new knowledge extracted from the data available in the graph database. The plugin is open-sourced under GPL and aims to provide a complete end-to-end customized search framework with other plugins available on the GraphAware products page.
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