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230 Selected Studies on Software and Information Systems
– Selection – web-based information systems often display a list of results, each with
only a brief description. Selection of one particular result for further examination
provides information about user’s interest.
– Duration – as positive correlation was found between reading time and and explicit
rating in USENET applications (as cited in [51]), we can consider duration as another
aspect determining user’s interests.
– Read wear – extends the duration aspect by including the idea of “computational
wear”, which informs us about reading history of the document (e.g., which parts
were read and which were just scrolled) [30].
– Repetition – repetitive behavior in exploring information space.
– Purchase – represents user’s decision to perform some additional action with the item
such as purchase, print, add to bookmarks etc. It is a strong indication of a positive
feedback.
An example of work with implicit feedback is [17] in which authors were creating a model
of a museum visitor to provide personalized reports about a particular museum visit. Each
visitor possesses an electronic guide during the visit. Implicit feedback is represented by
pressing keys “More” (positive feedback) or “Enough” (negative feedback) during the commentary.
By pressing “More”, user gets further, more detailed information about particular
exhibit. As a side effect, system is informed about user interests. By pressing “Enough”,
user can interrupt the commentary on particular exhibit (which is interpreted as a negative
feedback). Also the fact, that the user did not interrupt the commentary can be considered as
rather positive feedback. The “More” button represents Selection from the above mentioned
classification. Usage of “Enough” button is related to Duration.
Implicit feedback was used also in project Casper [56] in the domain of job offers. Authors
use three metrics to estimate implicit feedback: re-visiting an offer, time spent reading an
offer and further activities related to an offer (applying for a job, sending an offer via e-mail).
Focus is given on log preprocessing, to leave out unwanted events such as multiple clicks on
one offer, which should not be considered as a re-visit if it was caused by user’s impatience
or correction of an offer reading time according to mean reading time.
The analysis of user behavior is discussed also in [38]. Authors examine time related
information (implicit feedback Duration) in an e-Learning course, where students have possibility
to listen to the lectures and watch handouts.
Monitoring User Behavior This approach covers the implicit feedback acquisition approach,
but is not restricted to feedback related behavior and tracks a complete behavior of
the user within a system. The main difference is that the system records as many actions
as possible such as the time the user spent viewing a particular page, the way the user
navigates on a web site, clickstreams, list – detail transactions, page reading (i.e., scrolling
down the page), eventually usage of active page element (e.g., hover) or additional system’s
functionality (e.g., adding a publication to Favorites).