Alfred Kobsa
Selected
Research Projects
Cooperation Awareness and Privacy
This project aims at supporting distributed workgroups
negotiate a policy for disseminating awareness information. This policy
should balance the demand for such information with individual privacy preferences.
| Researchers: |
Alfred Kobsa (Faculty)
Sameer Patil (Ph.D. student)
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| Duration: |
Since July 2002 |
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| Funding: |
NSF (as part
of a "mid-size" ITR grant)
NSF (for collaboration with the European PRIME project)
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| Results: |
C34, C36, B16, O15
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Privacy as a Design Requirement for Personalized Systems
Privacy demands of Internet users and international (and future national)
privacy legislation have an impact on the collection of personal data in
web-based systems. This project studies specifically the impacts on "personalized"
web-based systems, which cater their interaction to each individual user,
collect considerable amounts of personal data for this purpose, and "lay
them in stock" for possible future adaptation. This project analyzes and
documents these privacy requirements.
| Researchers: |
Alfred Kobsa (Faculty)
Yang Wang (Ph.D. student)
Max Teltzrow (visiting Ph.D. student)
Zhaoqi "Stella" Chen (Ph.D. student)
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| Duration: |
Since Oct. 2001 |
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| Funding: |
CRITO (2001-03), NSF (since
July 2003), Humboldt Foundation (since
Oct. 2004, for collaboration with Humboldt
University) |
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| Results: |
J17, C25,
B15,
W15, W16, W17,
W18, W19
Catalog
of requirements imposed by international privacy laws |
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Privacy through Pseudonymity in User-Adaptive
Systems
Adaptive systems are generally better able to cater to users the more data
their user modeling systems collect and process about them. This project
analyzes security requirements to guarantee privacy in user-adaptive systems
and explores ways to keep users anonymous whilst fully preserving personalized
interaction with them. User anonymization in personalized systems goes beyond
current models in that not only users must remain anonymous but also the
user modeling system that maintains their personal data. Moreover, users'
trust in anonymity can be expected to lead to more extensive and frank interaction,
hence to more and better data about the user, and thus to better personalization.
A reference model for pseudonymous and secure user modeling has been developed
and implemented that meets many of the proposed requirements.
Success Factors of Information Visualization Systems
Research in information visualization aims at leveraging human perceptual
abilities for data analysis, by presenting information not as numbers and
text but in visual form. Effective visual displays must therefore be designed
in such a way that users can easily obtain an overview of the data, spot outliers,
patterns and correlations, and see the changes that will occur if some parameters
become altered. Visualizations need to make such significant facts salient
for human perception. This identifies "success factors" of visualization
systems for multivariate data, by conducting experiments both with analysts
working individually on a computer screen, and with groups of analysts collaborating
in front of a large-sized display.
| Researchers: |
Alfred Kobsa (Faculty)
Victor Gonzales (Ph.D. student)
Several undergraduate students
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| Duration: |
Since Jan. 2001 |
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| Funding: |
CRITO |
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| Results: |
J21, C24, C27 ,
C29, C30, C31, C32, C35, O17
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User
Modeling as an Open Learning Process (LaboUr)
Generic user modeling systems so far pursued a strongly knowledge-based
approach. Heuristics regarding assumptions that can be made about users when
certain observations were made about them had to be empirically found beforehand
and expressed in knowledge representation mechanisms. The project LaboUr developed
a generic prototype that incorporated user modeling as an open learning process.
"Open" thereby means that the user modeling system can process any kind of
assumption about the user, and can communicate with any kind of source that
provides information about the user. Learning "process" refers to the continuous
incremental processing, abstraction and revision of assumptions about the
user based on the observed user behavior.
| Researchers: |
Alfred Kobsa (Faculty)
Wolfgang Pohl (Post-Doc.)
Ingo Schwab (Ph.D. student)
Ramin Yasdi (Researcher)
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| Duration: |
Aug. 1997 – Nov. 2000 |
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| Funding: |
German Research Foundation |
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| Results: |
J18, W12
Schwab I., Pohl W. and Koychev, I. (2000). Learning to
Recommend from Positive Evidence, Proceedings of Intelligent User Interfaces
2000, ACM Press, 241-247.
Pohl W. (1997). LaboUr - Machine Learning for User Modeling. Proc. of
the Seventh International Conference on Human-Computer Interaction.
Amsterdam: Elsevier. |
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Adaptive and Adaptable Interactions for Multimedia
Telecommunications (AVANTI)
The World Wide Web is going to be the leading online information medium
for some years to come and will most likely become the standard gateway for
citizens to the “information highway”. Already today, visitors of web sites
are generally heterogeneous and have different needs, and this is likely
to increase in the future. The aim of the AVANTI project in which 12 organizations
collaborate is to cater hypermedia information to these individual needs
by adapting the content and the presentation of web pages to each individual
user. The special needs of elderly and disabled users are also partly considered.
A model of the characteristics of user groups, individual users and usage
environments, and a domain model are exploited in the adaptation process.
One aim of this research is to verify that adaptation and user modeling techniques
that were hitherto mostly used for catering interactive software systems
to able-bodied users also prove useful for adaptation to users with special
needs. Another original aspect is the development of a network-wide user
modeling server that can concurrently accommodate the user modeling needs
of several applications and several instances of an application within a
distributed computing environment.
| Researchers: |
Alfred Kobsa (Faculty)
Josef Fink (Ph.D. student)
Andreas Nill (Ph.D. student)
Igor Jaceniak (Researcher)
Armin Hüttenhain (Researcher)
Gabriele Nordbrock (Researcher)
Several undergraduate students
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| Duration: |
Aug. 1995 – Nov. 1999 |
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| Funding: |
European Commission (ACTS Programme)
Collaborative research of 12 institutions |
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| Results: |
J12,
C14, C15,
C16, C17,
C18, C19,
C20, C22,
B12, N10,
O11 |
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A User Modeling Shell System (BGP-MS)
This project developed BGP-MS, a user modeling shell system that can assist interactive
software systems in adapting to their current users by taking the users’
presumed knowledge, beliefs, and goals into account. It offers applications several
methods for communicating observations concerning the user to BGPMS, and for obtaining
information on currently held assumptions about the user from BGP-MS. It provides
a choice of two integrated formalisms for representing beliefs and goals, and
includes several types of inferences for drawing additional assumptions based
on an initial interview, observed user actions, and stereotypical knowledge about
pre-defined user subgroups. BGP-MS is a customizable software system that is independent
from applications, operates concurrently with them, and interacts with them through
inter-process communication. For tailoring BGP-MS to a specific application domain,
the developer must select those components of BGP-MS that are needed in this domain
and fill them with relevant domain-dependent user modeling knowledge.
| Researchers: |
Alfred Kobsa (Faculty)
Wolfgang Pohl (Ph.D. student)
Jörg Höhle (Ph.D. student)
Several undergraduate students
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| Duration: |
Feb. 1992 – Aug. 1997 |
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| Funding: |
German Research Foundation |
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| Results: |
J10, C12,
C13, C21,
C23, C26,
W6, W8,
W9, W10
Server software: ftp://ftp.gmd.de/gmd/bgp-ms
Draft standard: O10
Wolfgang Pohl (1997): Logic-Based Representation and Reasoning for User
Modeling Shell Systems. Berlin: Academic Publishing Corporation –
infix.
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A Natural-Language Access System to Expert
Systems (XTRA)
The XTRA access system to expert systems aims at rendering the interaction
with expert systems easier for inexperienced users. XTRA communicates with
the user in a natural language (German), extracts data relevant to the expert
system from his/her natural-language input, answers user queries as to terminology,
and provides user-accommodated natural-language verbalizations of results
and explanations provided by the expert system. A number of novel artificial
intelligence techniques have been emplozed in the development of the system,
including the combination of natural-language user input with user gestures
on the terminal screen, referent identification with the aid of four different
knowledge sources, simultaneous communication of the access system with the
user and the expert system, fusion of two complementary knowledge bases into
a single one, and the design of a natural-language generation component which
allows for a controlled interaction between the "what-to-say" and the "how-to-say"
parts to yield a more natural output. XTRA is being deveoped independenly
of any specific expert system. In its first application, the access to an
expert system in the income tax domain is being realized.
| Researchers: |
Wolfgang Wahlster (Faculty)
Alfred Kobsa (Co-director)
Roman Jansen-Winkeln (Ph.D. student)
Jürgen Allgaier (Ph.D. student)
Carola Reddig (Ph.D. student)
Dagmar Schmauks (Researcher)
Several undergraduate students
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| Duration: |
May 1985 – Sept. 1991 |
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| Funding: |
German Research Foundation |
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| Results: |
J5, J6,
J7, J8,
J9, C7,
C8, C9,
C10, C11,
B8, B9,
W1, W2,
W3, W4,
W5, N6,
N7, N8,
N9, O6 |
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