Recently, there has been a significant amount of interest in automatically
creating large-scale knowledge bases (KBs) from unstructured text. The
Web-scale knowledge extraction task presents a unique set of opportunities
and challenges. The resulting knowledge bases can have the advantage of
scale and coverage. They have been enriched by linking to the Semantic Web,
in particular the growing linked open dataset (LOD). These semantic
knowledge bases have been used for a wide variety of Natural Language
Processing, Knowledge Representation, and Reasoning applications such as
semantic search, question answering, entity resolution, ontology mapping
etc. The automatic construction of these KBs has been enabled by research
in areas including natural language processing, information extraction,
information integration, databases, search and machine learning. There are
substantial scientific and engineering challenges in advancing and
integrating such relevant methodologies.
With this year’s workshop, we would like to resume the positive experiences
from several previous workshops: AKBC-2010, WEKEX-2011 and the joint
AKBC-WEKEX-2012. This workshop will serve as a forum for researchers
working in the area of automated knowledge harvesting from text. By having
invited talks by leading researchers from industry, academia, and the
government, and by focusing particularly on vision papers, we aim to
provide a vivid forum of discussion about the field of automated knowledge
base construction.
Topics of Interest
Topic of interest include, but are not limited to:
information integration; schema alignment; ontology alignment;
ontology construction
monolingual alignment, alignment between knowledge bases and text
joint inference between text interpretation and knowledge base
pattern and semantic analysis of natural language, reading the web,
learning by reading
scalable computation; distributed computation; probabilistic
databases
information retrieval; search on mixtures of structured and
unstructured data
machine learning; unsupervised, lightly-supervised and
distantly-supervised learning; learning from
naturally-available data
human-computer collaboration in KB construction; automated population
of wikis
dynamic data, online/on-the-fly adaptation of knowledge
inference; scalable approximate inference
languages, toolkits and systems for automated knowledge base
construction
demonstrations of existing automatically-built knowledge bases
Important Dates
March 31, 2014 (11:59pm SST[UTC -11 hours]): Paper submission
deadline
April 27, 2014 Paper decision
May 27, 2014 Camera ready paper due
June 27, 2014 Workshop date
Submission Information
We welcome ongoing and exciting preliminary work. We are particularly
interested in visionary paper submissions. We aim for papers that express
intriguing and promising ideas — focusing less on where science is today
and more on where it should go tomorrow.
Please format your papers using the ACM Proceedings Format, using one of
the templates provided at
http://www.acm.org/sigs/pubs/proceed/template.html for Word and LaTeX
(version 2e). (For LaTeX, both Option 1 and Option 2 are acceptable.) The
font size, margins, inter-column spacing, and line spacing in the templates
must be kept unchanged. and restrict it to 4 pages (excluding references).
Reviewing will be double-blind, so please remove author names and
affiliations, and also any self references that might reveal author
identities. All accepted papers will be presented as posters. Additionally,
the top 3 papers as determined by the PC will also be presented in an oral
session.
Please submit your papers at
https://www.easychair.org/conferences/?conf=wacck2014 by March 27, 2014.
Invited Talks (more to come)
Kevin Murphy (Google)
Lise Getoor (University of California, Santa Cruz)
Organizing Committee
James Fan (IBM)
Evgeniy Gabrilovich (Google)
Chris Jermaine (Rice University)
Aditya Kalyanpur (IBM)
Chris Re (Stanford University)
Program Committee (more to come)
Michael Cafarella (University of Michigan)
Peter Clark (Vulcan Inc, US)
Tony Fader (University of Washington)
Ruihong Huang (University of Utah)
Lise Getoor (University of California, Santa Cruz)
Bonan Min (BBN, US)
Patrick Pantel (Microsoft Research)
Sebastian Riedel (University College of London)
Sunita Sarawagi (IIT Bombay)
Ioana Stanoi (IBM Research)
Martin Theobald (Max-Planck-Institut für Informatik, Germany)
Daisy Zhe Wang (University of Florida)
Limin Yao (University of Massachusetts)