Non-Text Discovery with ConceptNet as a Neo4j Database [Community Post]

The ConceptNet dataset is a semantic network built from nodes representing words or short phrases of natural language, with relationships between them. It aims to enable systems to take human words as input and use them to better search for information, answer questions, and understand user goals. The concept can be applied in various domains such as retail, social startups, and content platforms, where tag-based recommendations and categorizations are used. By translating the ConceptNet5 API into a graph database, it takes away the agony of tag-based recommendations and provides insights on how to categorize products effectively. The dataset is incredibly rich, providing various "senses" in which someone might mean a word and offers a wide variety of relationship types to choose from.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.