Our-Hometown's Related Stories block appears at the end of each Article on your website and aims to keep readers engaged with your website by recommending similar articles that the reader might be interested in. Unlike similar "Recommended Articles" systems that simply suggest another article from the same category as the one the reader has just finished reading, our Related Stories block uses the context within the article to generate a list of articles that the reader is most likely to want to read.

Highlights

The main advantage to Our-Hometown's Related Stories block is that while other solutions simply recommend articles that are assigned to the same category as the one being viewed, Our-Hometown's uses the context of each article to generate a list of similar stories that would be of interest to the reader. This is achieved by using Natural Language Processing to analyze and identify Named Entities within each story published to your website. These Named Entities allow us to create semantic connections between stories and group them together based on the relationships between people, places, and organizations mentioned within each article.

Uses Natural Language Processing to identify the Named Entities of every story on the website and provide matches based on topic overlap
- Named Entities are categorized as follows:
  - PERSON - People, including fictional.
  - NORP - Nationalities or Religious or Political Groups
  - FAC - Buildings, airports, highways, bridges, etc.
  - ORG - Companies, agencies, institutions, etc
  - GPE - Countries, cities, states
  - LOC - Non-GPE locations, mountain ranges, bodies of water
  - PRODUCT - Vehicles, weapons, foods, etc (not services)
  - EVENT - Named hurricanes, battles, wars, sports events, etc.
  - WORK OF ART - Titles of Books, songs, etc.
  - LAW - Named Documents made into laws
  - LANGUAGE - Any named language