The Semantic Web 10th Year Update
The talk will
be based on the fact that the Scientific American article by Tim
Berners-Lee, Ora Lassila and James Hendler was published on May 21,
2001. The WIMS'11 conference is an appropriate event to reflect on the
10 years - successes and misses.
Tetherless World Professor
of Computer and Cognitive Science, and the Assistant Dean for
Information Technology, at Rennselaer. He also serves as the
Associate Director of the Web Science Research Initiative headquartered
at MIT and is a visiting Professor at the Institute of Creative
Technology at DeMontfort University in Leicester, UK.
technical papers in the areas of artificial
intelligence, Semantic Web, agent-based computing and high performance
processing. One of the inventors of the "Semantic Web," Hendler was the
recipient of a 1995 Fulbright Foundation Fellowship and is a Fellow of
the American Association for Artificial Intelligence and the British
Computer Society. He is the Editor-in-Chief emeritus of IEEE
Intelligent Systems and is the first computer scientist to serve on the
Board of Reviewing Editors for Science.
Open Social Learning Communities
With the advent of open
education resources, social networking technologies and new pedagogies
for online and blended learning, we are in the early stages of a
significant disruption in current models of education. The disruption
is fueled by a staggering growth in demand. It is estimated that there
will be 100 million students qualified to enter universities over the
next decade. To educate them, a major university would need to be
created every week.
Universities have responded to this need with Open Education
Resources—thousands of free, high quality courses, developed by
hundreds of faculty, used by millions worldwide. Unfortunately, online
courseware does not offer a supporting learning experience or the
engagement needed to keep students motivated. Students read less when
using e-textbooks; video lectures are boring; and retention and course
completion rates are low.
Therein lies the core problem: How to engage a generation of learners
who live on the Internet yet tune out of school, who seek interaction
on Facebook yet find none on iTunes U, who need community yet are only
offered content. We propose a new approach to this problem: open social
learning communities anchored with open content, providing an
interactive online study group experience akin to sitting with study
buddies on a world-wide campus quad.
This solution is enabled by state-of-the-art web technologies: really
real-time collaboration technologies for a highly interactive
experience; intelligent recommender systems to help learners connect
with relevant content and other learners; mining and analytics to
assess learner outcomes; and reputation techniques to establish social
capital. We will discuss these technologies and how they can be
combined to address the problem of education in a manner that is highly
scalable yet interactive and engaging.
This talk represents joint work with Preetha Ram (Emory University),
Hua Ai (Georgia Tech), Chris Sprague (OpenStudy), and Saurav Sahay
the Cognitive Computing Lab and Associate Professor in the
College of Computing at Georgia Tech, and an Adjunct Professor in
Psychology at Georgia Tech and in MathCS at Emory University. He
received his PhD from Yale University in 1989, his MS from University
of Illinois in 1984, and his BTech from IIT Delhi in 1982.
| He has published 2 books and
over 100 scientific articles in international forums. He is a founder
of Enkia Corporation which develops AI software for social media
applications, and OpenStudy.com which is an online social learning
network for students and faculty.
Many Faces of Text Processing
people process text with computers? It all started many years ago, with
the main goal in minds of researchers, to understand the text. In the
meantime, the area of text processing developed in many different
directions whereby the original goals were often forgotten. Funny
enough, it seems, in several decades of computerized processing of
textual data, the solution to the 'text understanding' problem didn't
evolve much compared to some other, easier and often more profitable
problems to deal with (such as information retrieval/search, machine
translation or information extraction). In this paper we touch various
aspects of text processing along several dimensions: (a) how we
represent the textual data, (b) what kind of algorithms and techniques
we use, and (c) what kind of problems we solve on the top of text.
Finally, it is interesting to observe various research communities
dealing with textual data in different ways. Most of them are still
rather fragmented and don't learn enough from each other ‐ many of the
ideas developed within one community don't cross borders of that
community for too long.
||Marko Grobelnik is an expert in analysis of
large amounts of complex data with the purpose to extract useful
knowledge. In particular, the areas of expertise comprise: Data Mining,
Text Mining, Information Extraction, Link Analysis, and Data
Visualization as well as more integrative areas such as Semantic Web,
Knowledge Management and Artificial Intelligence.
aspects of unconventional data analysis techniques, he
has valuable experience in the field of practical applications and
development of business solutions based on the innovative technologies.
Marko was employed as a researcher first, at the Computer Science
Department at University of Ljubljana and later at the Department of
Knowledge Technologies at J. Stefan Institute, Ljubljana , Slovenia .
His main achievements are from the field of Text-Mining, having a
leading role at research and development projects funded by European
Commission, having projects with industries including Slovenian
publishing house, Slovenian National and University Library and
companies such as Microsoft Research. He has published papers in
refereed conferences and journals, served in program committee of
international conferences and organized a series of international
events in the area of Text Mining, Link Analysis and Data Mining .
Making Things Findable
The publishing of original
content on the Web and later, Web search have developed into two of the
most protable sources of business on the Web, supported by revenue
from display advertizing and search advertizing, respectively. Despite
a traditional separation, what we can observe on the Web today is a
gradual blurring of the lines between these two businesses as search
engines gradually integrate more and more structured content, and
online publishers turn to methods of search for customizing user
experiences. This brings both opportunities and a new set of challenges
in applying semantic technologies.
data architect at
Research in Barcelona, working on the applications of semantic
technology to Web search. His interdisciplinary work in social networks
and the Semantic Web earned him a Best Paper Award at the 2005
International Semantic Web Conference and a First Prize at the 2004
Semantic Web Challenge.
he has been a co-chair of
the Semantic Web Challenge. Mika is the youngest member elected to the
editorial board of the Journal of Web Semantics. He is the author of
the book 'Social Networks and the Semantic Web' (Springer, 2007).
In 2008 he has been selected as one of "AI's Ten to Watch" by the
editorial board of the IEEE Intelligent Systems journal.
of Interlinked Data
Over the past 4
years, the semantic web activity has gained momentum with the
widespread publishing of structured data as RDF. The Linked Data
paradigm has therefore evolved from a practical research idea into a
very promising candidate for addressing one of the biggest challenges
in the area of the Semantic Web vision: the exploitation of the Web as
a platform for data and information integration.
To translate this initial success into a world-scale reality, a number
of research challenges need to be addressed: the performance gap
between relational and RDF data management has to be closed, coherence
and quality of data published on the Web have to be improved,
provenance and trust on the Linked Data Web must be established and
generally the entrance barrier for data publishers and users has to be
lowered. This talk will discuss approaches for tackling these
challenges and their integration into a mutual refinement cycle - the
"linked data washing machine".
Auer leads the
group Agile Knowledge Engineering and Semantic
Web (AKSW) at Universität Leipzig. His research interests include
semantic data web technologies, knowledge representation, engineering
& management, as well as databases and information systems. He
50 peer-reviewed scientific publications.
large-scale integrated EU-FP7-ICT research
project "LOD2 - Creating Knowledge out of Interlinked Data". Sören
is founder (respectively co-founder) of several high-impact research
and community projects such as the Wikipedia semantification project
DBpedia or the social Semantic Web toolkit OntoWiki. He is co-organiser
of several workshops, programme chair of I-Semantics 2008, OKCON 2010,
ESWC 2010 and ICWE 2011, area editor of the Semantic Web Journal,
serves as an expert for industry, the European Commission, the W3C and
is member of the advisory board of the Open Knowledge Foundation.