- In word processing tasks
You are writing a document, it identifies which type (i.e dissertation, thesis, blog post,...) and then as you're writing away it identifies topic. You can highlight a word or a sentence and it delivers, within the application, relevant information about not "search" but "information need". It can deliver citations at will, summaries, direct answers and documents, as well as suggest related information and topics. This will make it possible to write and research super quickly and in parallel.
- Results based on TOD
The engine will learn from your habitual information needs and propose results that it believes can be of use to you at that time of day - for example 8-6 you work, so you won't be looking at the same stuff as from 8-12. "Quantum" may bot bring up "physics" in the evening but rather the new Bond film. of course there's options to use a different profile.
- Aggregating all of your personal information
As much as we fight against applications that act like "Big brother", scanning all our information and using it...to meet our information needs better. I think that this is inevitable because ultimately the younger generation as Jay Adelson from Digg said, are much less concerned about it. Gathering information from your TV habits, shopping habits, what applications you use etc...could well affect your information provision.
- Affective computing
This area of computing was a little dismissed at first but now its use is being increasingly understood. It involves finding out how the user feels during the information provision and search task. This means that they can counter negative feelings during the process. What things make you happy when you interact with them and which ones do you hate.
- Social networks
Not a new idea by any means but still an interesting one, which is being slowly put into motion right now. This is all about figuring out what social groups you belong to, what things you have in common with them, and what kind of interaction you have with them (swapping documents, videos, product information...). This adds to the personalised database that exists to improve your information provision.
Personalisation has many dimensions and used in isolation they cannot be effective. Nicholas Belkin recently identified some of these, stating what the Grand Challenges of IR were. We're looking at a future of mass information gathering on users and certainly improved information provision. The information is also going to be provided within task environments and will not make you go and visit another site to get what you need.
For SEO this means a big change in the way that we work. Interacting with users, providing interactive environments, highly informative content and also spontaneous information provision (rather than a site scan) is going to be very important. Traditional SEO will always have its place but as we see new algorithms come into play, we will need to adapt and move on.
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