Attention economy, the implicit web and myware

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The term attention economy describes an actual trend: the increasing “wealth of information creates a poverty of attention”. The separation of important information from the unimportant noise becomes more and more crucial.

We are leveraging the experience of other users, who sacrificed their attention before, and voted implicitly on the content they visited. This saves our time; we can focus on consuming already preselected, relevant information instead of searching for the needle in the haystack again. FAROO uses this wisdom of crowds for its user generated, user centric, attention based ranking.

To find the most relevant information possible, we have to rate the whole web. To ensure an objective ranking, each document has to be rated by many people. But the extra time required for manual voting would prevent the majority of visitors to vote on every document they visit or to vote at all. Only an automatic, implicit rating ensures that each visitor votes for each document he visits.
This is what the implicit web is about. Analyzing our behavior and using traces left during our journey through the web, we are voting automatically on the fly, implicit without manual action. An interesting blog post of Alex Iskold of Read/WriteWeb illustrates this further.

While this seems a useful thing, it raises privacy concerns. We feel and fear our privacy is once more fading away. But than, myware reconciles personalization and privacy. Myware is tracking our behavior, but is not revealing it to any third party, but using it solely to benefit the user.

This describes perfectly the approach of FAROO to use all the implicit information in order to cope with the information overflow and to improve the search experience for the user, without sacrificing privacy. A as the information is not leaving the computer, there is no risk this data could be sold, handed over or leaked from a central repository.

FAROO utilizes the implicit web to direct the crawler to places the users are interested in, to select, rank and personalize results according to the attention users paid to the content visited, and to implement behavior targeting for advertising based on present and past behavior.

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