Personalization involves using technology to accommodate the differences between individuals, such as greeting the user by name or varying content according to what you know about the user's interests. Personalization implies that the changes are based on implicit data, such as items purchased or pages viewed. The term customization is used instead when the site only uses explicit data such as ratings or preferences.
Personalization involves using technology to accommodate the differences between individuals. Web pages are personalized based on the characteristics (interests, social category, context, ...) of an individual. Personalization implies that the changes are based on implicit data, such as items purchased or pages viewed. The term customization is used instead when the site only uses explicit data such as ratings or preferences.
There are three categories of personalization:
- Profile / Group based
- Behaviour based (also known as Wisdom of the Crowds)
- Collaboration based
Web personalization models include rules-based filtering, based on "if this, then that" rules processing, and collaborative filtering, which serves relevant material to customers by combining their own personal preferences with the preferences of like-minded others.
Collaborative filtering works well for books, music, video, etc. However, it does not work well for a number of categories such as apparel, jewelry, cosmetics, etc. Recently, another method, Prediction Based on Benefit, has been proposed for products with complex attributes such as apparel.
There are three broad methods of personalization:
- Implicit
- Explicit
- Hybrid
With implicit personalization the personalization is performed based on the different categories mentioned above. With explicit personalization, the web page (or information system) is changed by the user using the features provided by the system. Hybrid personalization combines the above two approaches to leverage "the best of both worlds".
