FAQs

What is the Anteriad's Topic Score Methodology?

The Anteriad Topic scoring methodology uses multiple techniques and dimensions to determine the score.

Examples of techniques that are used are as follows:

Natural Language Processing (NLP) is used to prepare and cleanse incoming signal data.
Machine Learning (ML) is used to associate URLs/Domains, keywords, and 'search on page' to a topic. For example, Microsoft Azure = Cloud Computing
There are many dimensions used within our model but simple example would be the the number of unique signals seen in relation to the employee size for the company location or site. Overall we leverage more than 100 attributes in the model from industry, to ip adress.
The model uses a point in time or a window of time where zero signals for any employee size of say 100 would result in a zero topic score. In contrast signals 100x of the employee size might result in a score of 100.

All scoring done at a site level not at a domain level i.e. Oracle 100 Oracle Pkwy, Redwood City, CA 94065 (address) vs. Oracle Global (list)