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236 Selected Studies on Software and Information Systems
and provides a ranked list of similar users from the very beginning of user’s work with the
system (so the system is able to provide also collaborative filtering based on users similarity).
During the usage of the system, user browsing behavior is monitored via a proxy server,
where each URL browsed during normal work activity is logged. A classifying algorithm is
used to classify browsed URL’s based on a training set of labeled example papers, storing
each new paper in a central database. The profiling algorithm performs correlation between
paper topic classifications and user browsing logs. Whenever a research paper is browsed
that has been classified as belonging to a topic or an explicit feedback on recommendation is
provided, it accumulates an interest score for that topic. This is the way Quickstep contributes
back to the bootstrap ontology.
The weak point of the approach is the assumption that ontology used for bootstrap contains
knowledge about the new user and that this user has already written some publications
which could be compared with publications in the information space.
User Model Mediation
The concept of mediation of partial user models between several adaptive systems was proposed
in [8]. The basic idea is that different applications would benefit from enriching their
UMs through importing and aggregating user models which were built by other, possibly
related applications. It is different from the centralized user model approach using user
modeling server, where each application extracts the required data from the central UM
and updates it later. The described approach is designed to be decentralized and providing
ad-hoc (for a specific purpose) generation of user model for the target application through
translation and aggregation of partial UMs built by other applications. It is therefore useful
for solving cold-start problem.
The mediation to be successful needs to solve several issues among which is user’s
privacy, the structural heterogeneity and incompleteness of the user models content, since
every application refers to a specific application domain only.
The mediation process is partitioned to the following stages (see Figure 8-8):
1. A target application, required to provide personalization to a user, queries the mediator
for the user model related to the application domain.
2. The mediator identifies the required personalization domain and the user model
representation in the target application.
3. The mediator determines a set of other applications that can potentially provide partial
domain-related user models of the given user and queries them.
4. Applications, actually storing the needed data, answer the query, and send to the
mediator their partial user models of the given user.
5. The mediator translates and aggregates the acquired partial user models (using the
knowledge base (KB)) into a single domain-related user model, represented according
to the target application.
6. The generated domain-related user model is sent to the target application, which is
capable of providing more accurate personalized service.