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KNOWLEDGE
APIS – Advanced Personalization in Information Services
The Personal Essence of Queries
Human choices are guided by individual preferences.
In initiating the decision process, we usually
have no idea about the optimal choice or its
potential impact. Nevertheless, we often have
an intuitive understanding of relative desirability.
By repeated comparisons between alternatives
we get a clear picture of what we are
actually looking for. Since more and more information
is stored digitally, support for preferen-
Motivation
Today many e-commerce companies assist their customers
with digital shopping aids. A very successful type of shopping
aid are recommender systems. Typically, these systems
evaluate product ratings given by a large set of customers.
Shopping recommendations are then generated
by finding users that are similar to the target customer who
is requesting a recommendation. Well-known examples of
such systems are: Amazon “Customers Who Bought This
Item Also Bought” feature; and the movie recommendations
given by the DVD rental service Netflix.
Although predictions made by recommender systems are
often quite impressive, they have limitations. Since these
systems rely on implicit similarities between customers
and items, they are the tool of choice, whenever no other
explicit preferential information is available. This can be
clearly seen in the case of movies and books, where describing
items apriori within a fixed attribute scheme (e.g. by
quantifying the amount of humor, action, and suspense) is
difficult and pointless for inherently subjective tasks. In contrast,
when comparative choices are desired, recommendations
should take into account preferential statements such
as: “I like Audi better than Volkswagen”. Unfortunately, current
recommender systems cannot do that, and there are
no convincing alternatives available.
The APIS project investigates the design of recommendation
algorithms based on explicit preference statements.
A major goal is to integrate this functionality into standard
database technology, since product databases or catalogs
FORSCHUNGSZENTRUM L3S L3S RESEARCH CENTER
tial choice processes in database technology is
essential for supporting sound decision-making.
unfortunately, current database systems
force users to provide a precise description of
information needs, which they often are unable
to provide. The goal of the APIS project is to
equip databases with features and tools for
closing this “preference gap”.
The APIS group at L3S Research Center investigates
how the handling of human preferences
can be integrated into current database systems.
The goal of APIS is to equip databases with the
capabilities to answer the user’s queries in a personalized
fashion. Currently, research within APIS
focuses on efficient query processing, preferences
regarding compromises, and intuitive methods of
user interaction.
provide the main area of application. Furthermore, database
integration is the only way to make explicit preference
handling easily available to a broad range of users.
Challenges
The most important challenges within APIS are performance,
effectiveness, and usability. These factors translate
into strict requirements when it comes to building a successful
preference-based database system:
• The system must be fast and able to process large
amounts of data, since more and more digital information
is available every day and users want to have their
queries answered immediately.
• The system must produce reasonable and comprehensible
results, since users will only trust a system that is