Personalization involves using technology to accommodate the differences between individuals. Once confined mainly to the Web, it is increasingly becoming a factor in education, healthcare (i.e. personalized medicine), and both "business to business" and "business to consumer" settings.
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.
On an intranet or B2E Enterprise Web portals, personalization is often based on user attributes such as department, functional area, or role. The term customization in this context refers to the ability of users to modify the page layout or specify what content should be displayed.
There are three categories of personalizations:
1. Profile / Group based
2. Behaviour based
3. 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[1].
There are three broad methods of personalizations:
1. Implicit
2. Explicit
3. Hybrid
With implicit personalization the personalization is performed by the web page (or information system) 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 for leverage best of both worlds.
Many companies offer services for web recommendation and email recommendation that are based on personalization or anonymously collected user behaviors. Following the example of Amazon.com, the online retailing industry has been early adopters of 3rd party personalization tools offered by companies like iGoDigital and Certona. Other 3rd party vendors like Choice Stream or Vignette bring personalization to content and display advertising.
Web personalization is closely linked to the notion of Adaptive hypermedia (AH). The main difference is that the former would usually work on what is considered an Open Corpus Hypermedia, whilst the latter would traditionally work on Closed Corpus Hypermedia. However, recent research directions in the AH domain take both closed and open corpus into account. Thus, the two fields are closely inter-related.
Personalisation is also being considered for use in less overtly commercial applications to improve the user experience online [2]. |
