Understanding Article Clusters
Our article clustering system leverages advanced algorithms to automatically group similar articles together. This provides valuable insights into trending topics, audience interests, and the evolution of content over time.
Cluster Overview
Currently, we have identified 7 major clusters based on content similarity. These clusters represent areas of significant interest within our article library.
Methodology
The system employs a combination of Natural Language Processing (NLP) techniques, including TF-IDF, Word Embeddings, and hierarchical clustering. This allows us to accurately capture semantic relationships between articles.
Recent Cluster Activity
Here's a snapshot of the most active clusters over the past week.
Cluster 1: Articles related to "Sustainable Living" - 125 new articles
Cluster 2: "Technology Trends" - 98 new articles
Cluster 3: "Financial Markets" - 72 new articles