DOCTORAL ABSTRACT

Interactive Exploration of Multi-Dimensional
Information Spaces with Preference Support
Panagiotis Papadakos
Computer Science Department, University of Crete, Greece
papadako@ics.forth.gr
Abstract
Users access large amounts of information resources mainly through search functions,where they type a few keywords and the web search or query engine returns a linear listof hits. While this is often satisfactory for focalized search, it does not provide enoughsupport for exploratory information needs. Faceted and Dynamic Taxonomies (FDT) isa highly prevalent model for exploratory search, which allows users to get an overview of
the information space and offer them various groupings of the results based on their attributes, metadata, or other dynamically mined information, enabling them to gradually
restrict their focus through clicks and locate low ranked resources. The enrichment of suchmechanisms with preferences could be proven useful for exploratory tasks. However, the current preference-based approaches seem to ignore the fact that users should be acquainted with
the information space and the available choices for describing effectively their preferences.
In this dissertation we extend the interaction model of FDT with preference actions thatallow users to express their preferences interactively, gradually, and in a simple way. We
introduce a preference framework appropriate for information spaces comprising resources
described by attributes whose values can be hierarchically valued and/or multi-valued. We
define the language, its semantics and the required algorithms. The framework supports
preference inheritance in the hierarchies, automatic conflict resolution, as well as preference composition. Subsequently, we enrich the FDT model with preference actions and we
propose logical optimizations and methods for exploiting the intrinsic characteristics of theFDT-based interaction, aiming at making it applicable to large amounts of information. We
present the design and the implementation of the web-based system Hippalus, which realizes
the extended interaction model. Regarding user benefits, we theoretically analyze user gainin terms of the number and difficulty of choices, and we describe and analyze three user-basedevaluations. The first investigates the degree of effectiveness of preferences when users are
not aware of the available choices. We found that only 20% of the users managed to express
effective preferences without knowing the available choices. The second comparatively evaluates FDT with other exploratory models, and shows that the majority of users preferred
FDT, was more satisfied by FDT and achieved higher rates of task completion with FDT.
The last one evaluates the preference-enriched FDT as realized by Hippalus. The results
were impressive. Even in a very small dataset, with the preference-enriched FDT all users
successfully completed all tasks in 1/3 of the time and with 1/3 of the actions in comparison
to the plain FDT. Moreover all of the users preferred the preference-enriched interface.
Available: http://www.ics.forth.gr/_publications/Papadakos_Dissertation.pdf

ACM SIGIR Forum118

Vol. 48 No. 2 December 2014