Keynote Speaker |
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Computer
Vision: AI or Non-AI Problem
Takeo Kanade, Carnegie Mellon University, USA
Vision is one of the first areas that Artificial
Intelligence tackled. Today, however, it appears as if the two fields,
Computer Vision and Artificial Intelligence, have very little interaction,
and the goal of developing a general vision system, such as understanding
natural scenes, continues to be least understood or is almost abandoned.
This talk will start with Dr. Kanade's historical perspectives on
how this happened, and then present the argument that there is an
opportunity to renew the tie between the two fields for the purpose
of developing a capable AI-based vision system. |
AI and the Web - Special Track
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The
Past, Present and Future of Web Information Retrieval
Mehran Sahami, Google, Inc. and Stanford University,
USA
Web search engines have emerged as one of the central
applications on the Internet. In fact, search has become one of
the most important activities that people engage in on the Internet.
Even beyond becoming the number one source of information, a growing
number of businesses are depending on web search engines for customer
acquisition. The first generation of web search engines used text-only
retrieval techniques. Google revolutionized the field by deploying
the PageRank technology - an eigenvector-based analysis of the hyperlink
structure - to analyze the web in order to produce relevant results.
Moving forward, Google's goal is to better allow users to obtain
relevant information through the deployment of a variety of technological
advances in information analysis, understanding, and retrieval.
This presentation will describe some of the main challenges encountered
in web information retrieval, some of the current techniques used,
and will offer an overview of the search engine of the future.
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Deploying
Information Agents on the Web
Craig Knoblock, University of Southern California,
USA
The information resources on the Web are vast,
but much of the Web is based on a browsing paradigm that requires
someone to actively seek information. Instead, one would like to
have information agents that continuously attend to one's personal
information needs. Such agents need to be able to extract the relevant
information from web sources, integrate data across sites, and execute
efficiently in a networked environment. In this talk, Dr. Knoblock
will describe the technologies his group has developed to rapidly
construct and deploy information agents on the web. This includes
wrapper learning for turning online sources into agent-friendly
resources, query planning and record linkage to integrate data across
different sites, and streaming dataflow execution to efficiently
execute agent plans. He will also describe how they applied this
work within the Electric Elves project to deploy a set of agents
for real-time monitoring of travel itineraries.
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Web
Intelligence (WI): A New Paradigm for Developing the Wisdom Web
and Social Network Intelligence
Jiming Liu, Hong Kong Baptist University and Web
Intelligence Consortium
Web Intelligence (WI), since it was coined in 2000,
has become a new direction for scientific research and development
that explores the fundamental roles as well as practical impacts
of Artificial Intelligence (AI) and advanced Information Technology
(IT) on the next generation of Web-empowered products, systems,
services, and activities.
In this talk, Dr. Liu will show a coherent,
global picture of what WI concerns and what are the top-priority
research agendas. He will examine Web Intelligence (WI) as a new
paradigm for developing the Wisdom Web and Web-supported social
network intelligence.
While highlighting the current state of WI
research and development, the talk will consist of the following
five parts:
Part 1: Characterizes intelligent Web agents
from various aspects.
Part 2: Considers Web mining and farming for Web intelligence as
a business intelligence solution.
Part 3: Gives new directions in intelligent Web information retrieval.
Part 4: Focuses on Web knowledge management and infrastructure for
Web intelligent systems.
Part 5: Concerned with Web-supported social networks intelligence.
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Intelligent
Systems in Travel and Tourism
Hannes Werthner, eCommerce and Tourism Research
Lab (eCTRL)
ITC-irst and University of Trento, Italy
The talk will start by describing the travel and
tourism domain, with its very specific features. This will also
explain the importance of the sector in the e-commerce and e-business
domain, where travel & tourism is the number one application
domain (in b2c). Consequently, this industry depends heavily on
advanced IT. The characteristics of this marketplace will also serve
as the basis for presenting several application examples and running
projects. Many of them, quite naturally, follow an AI based approach:
travel planning and scheduling, visitor guidance systems, individual
pricing or reversed auctions, product bundling and recommendation,
or ontology based approaches to interoperability. In the final part
the presentation will provide a future outlook, based on the European
Research Vision of Ambient Intelligence and its applicability in
the travel and tourism domain.
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General Track
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Optimality
of Collective Choice in Social Insects and Social Robots
Jean-Louis Deneubourg, University Libre du Bruxelles,
Belgium
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Data
Integration: Successes and Challenges
Alon Halevy, University of Washington, USA
Integration of data from multiple sources is one
of the longest standing problems facing the AI and Database research
communities. In addition to being a problem in large enterprises,
research on this topic has been fueled by the promise of integrating
data on the WWW. In the past few years, we have made very significant
progress on data integration, from the conceptual and algorithmic
aspects, to the systems and product aspects. This talk will briefly
review our successes in data integration, and will describe some
significant current challenges. In particular, I will discuss the
problem of trying to semi-automatically find a semantic mapping
between a pair of schemas/ontologies, and argue that AI techniques
are crucial in this context. I describe an approach to schema matching
that is based on analyzing a large corpus of database schemas and
learning properties of how terms are used in database structures.
Finally, this talk will argue that such a corpus offers other exciting
opportunities for AI research.
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Constraint
Satisfaction, Databases, and Logic
Phokion G. Kolaitis, University of California,
Santa Cruz, USA
Constraint satisfaction problems constitute a broad
class of algorithmic problems that are ubiquitous in several different
areas of artificial intelligence and computer science. Indeed, constraint
satisfaction problems encompass Boolean satisfiability, graph colorability,
and numerous other problems in database theory, temporal reasoning,
machine vision, and belief maintenance.
In their full generality, constraint satisfaction problems are NP-complete
and, thus, presumed to be algorithmically intractable. For this
reason, extensive research efforts have been devoted to the pursuit
of "islands of tractability" of constraint satisfaction,
that is, special cases of constraint satisfaction problems for which
efficient algorithms exist.
The aim of this talk is to present an overview of recent advances
in the investigation of the computational complexity of constraint
satisfaction with emphasis on the connections of this area of research
with database theory and logic.
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Self-reconfiguring
Robots: Challenges and Successes
Daniela Rus, Dartmouth University, USA
We wish to create versatile robots by using self-reconfiguration:
hundreds of small modules autonomously organize and reorganize as
geometric structures to best fit the terrain on which the robot
has to move, the shape of the object the robot has to manipulate,
or the sensing needs for the given task. Self-reconfiguration allows
large collections of small robots to actively organize as the most
optimal geometric structure to perform useful coordinated work.
A self-reconfiguring robot consists of a set of identical modules
that can dynamically and autonomously reconfigure in a variety of
shapes, to best fit the terrain, environment, and task. Self-reconfiguration
leads to versatile robots that can support multiple modalities of
locomotion and manipulation. Self-reconfiguring robots constitute
large scale distributed systems. Because the modules change their
location continuously they also constitute ad-hoc networks. This
talk will discuss the challenges and successes of creating self-reconfiguring
robots, ranging from designing hardware capable of self-reconfiguration
to developing distributed controllers and planners for such systems
that are scalable, adaptive, and support real-time behavior.
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Automated
Verification = Graphs, Automata and Logic
Moshe Vardi, Rice University, USA
In automated verification one uses algorithmic
techniques to establish the correctness of the design with respect
to a given property. Automated verification is based on a small
number of key algorithmic ideas, tying together graph theory, automata
theory, and logic. In this self-contained talk, Dr. Vardi will describe
how this "holy trinity" gave rise to automated-verification
tools.
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New
Trends in Automated Reasoning
Andrei Voronkov, Manchester University, UK
This talk presents an overview of the past and
present of automated reasoning in first-order logic and tries to
predict how it will develop in the next several years. Dr. Voronkov
considers the theory of automated reasoning, implementation and
currently available systems, and applications. The presentation
will be centered around two main motives: (1) efficiency and (2)
usefulness for the existing and possible future applications.
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User
Interfaces: An AI Challenge
Daniel S. Weld,
University of Washington, USA
Today's computer interfaces are one size fits
all. Users with little programming experience have very limited
opportunities to customize an interface to their task and work habits.
Furthermore, the overhead induced by generic interfaces will be
proportionately greater on small form-factor PDAs, embedded applications
and wearable devices. Searching for a solution, researchers argue
that productivity can be greatly enhanced if interfaces anticipated
their users, adapted to their preferences, and reacted to high-level
customization requests. But realizing these benefits is tricky,
because there is an inherent tension between the dynamism implied
by automatic interface adaptation and the stability required in
order for the user to predict the computer's behavior and maintain
control. This talk will list challenges for the field, describe
principles governing effective adaptation, and present new algorithms
for data mining user action traces and dynamically transforming
interfaces.
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© Thomas Ramstorfer
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Quantum
Information: Fundamentals and Applications
Anton Zeilinger, Vienna University, Austria
The fundamental concepts in the emerging field
of quantum information are quantum superposition, entanglement and
the objective randomness of the individual event. Based on these
concepts the possible experimental realizations and possibilities
are discussed. These include quantum cryptography, teleportation,
quantum communication and quantum gates for future quantum computers.
All material will be presented in a way suitable for an audience
not familiar with quantum physics.
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* Please note that the talk titles are tentative
and subject to change
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