Entity Stuffing
Entity stuffing on a webpage is not different from keyword stuffing.
That’s why the focus should be on attributes of the main entity, instead of stuffing a webpage with entities of different types.
An entity may have a huge list of attributes.
And to deal with that long list there should be a prioritization criteria.
That criteria will help identify the most important attributes for processing on a webpage.
This is how I filter an entity's attributes to further process them.
🔥 Attribute Prominence:
An attribute is considered prominent for an entity if the entity cannot be defined or exist without it.
For example, the entity 'coffee' cannot exist without its following attributes:
- Origin
- Taste
- Types
Covering those attributes will be important for a source to become the topical authority state in the selected knowledge domain.
🔗 Attribute Relatedness:
This is a measure of how much an attribute is related to the source context.
Source context is the website purpose and the way a website monetizes its traffic.
In the Entity + Attribute pair [Coffee Filter], the filter attribute will be more related to a source selling coffee filters than a source selling coffee beans.
📊 Attribute Popularity:
It’ll be calculated by analyzing the search demand that an attribute has in the targeted region.
An attribute can have traffic potential but if it's not prominent or relevant, processing it on the source wouldn't make the sense.
Because traffic is not the ultimate goal of topical authority.
The ultimate goal is leads and revenue.
There might be instances where the data from queries doesn't properly match with the selected attribute of an entity.
The Solution?
Measuring the relatedness of an attribute with query patterns and synonyms in queries.
🎯 Final Note:
Whatever the attributes of an entity you chose to process, the goal should be to prioritize the most important attributes in the document for better contextual flow throughout the article while differentiating the macro and micro contexts from each other.