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I’m not you Modelling and conceptualizing personalization in information architecture Presented by / Bogo Vatovec Change Management / Knowledge Engineering / User Experience / Interaction Design / Process Engineering
Conceptualizing personalization has one basic rule Describe behaviour without and with personalization separately.
Separate behaviour without and with personalization Without personalization, the user experience looks like this….. With personalization, the user experience looks like that….. Personalization expands the existing essential functionality. It is never a function on its own. The interactive system must serve its main purpose also without personalization.
IAs use common usage scenarios to define the context of personalization
Modelling using aspects-orientation provides several advantages
Makes conceptualization and incremental detailing easier
Enables iterative development
Allows for functional reduction
Allows for easier testing and verification
This was easy, wasn‘t it? Wait – were are at the personalization rules? Wait – were are the Bayesian models? Wait – were are adaptive interfaces?
Personalization rules specify conditions when personalization applies
If user is looking at content A and content B has similar tags, show content B as related content.
If user A is looking at product 1 and has a similar profile to user B and user B also bought product 1 and bought product 2, recommend product 2 to user A.
If user A with profile A has click 1 then 2 then 3 and pauses for 2,5s here, show context sensitive help.
In the conceptualizing process, we use a simple descriptive language like this.
Notice example Number 2) – it has a sequence of conditions…. Will talk about this in a minute.
Let‘s move to technology a bit and then explore the rest
Personalization strategy defines the use cases for technology
Capture user behaviour on the website and store it in the user profile.
Dynamically generate content recommendations based on user behaviour in real time (in one session)
Dynamically generate content recommendations based on the stored user profile.
Provide for statistical analysis of user behaviour based on user profiles to expand marketing knowledge.
Provide the user the possibilities to customize the layout of the home pages.
To come up with requirements, you need to further specify them
Technical architecture for personalization Users User interface Layer Personalization Profile Layer Specific Values Vocabulary Layer Attributes Content User Profile Content Profile Content Attributes User Attributes Personalization Rules Personalization Rules Modified from the model by Argus Center for Information Architecture Analytics User Behaviour Content Statistics
How much does one system require explicit user profile setting?
How much implicit?
How does it integrate with other systems to fill out the profiles?
How does the system support vocabulary level personalization rules?
How easy it is to automatically populate content values?
What features does the personalization system include to manage controlled vocabularies?
Those of you who carefully listened notices that I missed an important compontent….. TIME
Until now we looked at the user and content profiles as one object with one state Since the user profile has only one state, we forget the sequence of actions – user‘s decision making process
Here the fun begins: Adaptive user interfaces and even – yes – artificial intelligence
Adaptive user interfaces are interfaces which automatically acquire knowledge about the users, update this knowledge over time, and uses this knowledge to adapt to the users’ requirements.
Artificial intelligence is defined as as "the study and design of intelligent agents, where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.