[CfP] 2nd call for HSSUES Workshop at ISWC 2017: deadline extended to Aug. 6!

*Hybrid Statistical Semantic Understanding and Emerging Semantics (HSSUES)*
<http://usc-isi-i2.github.io/ISWC17workshop/> is a full-day workshop being
held at ISWC this year. HSSUES is dedicated to exploring the synergy
between traditional semantic models like ontologies and schemas, and
emerging semantic models such as word embeddings through research,
experiment (including negative results) and resource contributions.

HSSUES will be a highly interactive workshop with participants from a wide
range of backgrounds, from researchers to application builders, and from
academia to industry. Researchers with an interdisciplinary interest in
exploring synergies between declarative semantics such as ontologies and
machine learning and knowledge discovery methods, especially graph
(including knowledge graph) embeddings and deep neural networks, are
especially invited to participate and submit papers. In addition to oral
presentations selected from submitted papers, we will have poster sessions,
and also a small number of invited talks from prominent researchers and
industry representatives. We also expect to have a couple of ‘position
talks’ laying out the view of hybrid systems from each of the perspectives.
HSSUES will also include a panel with panelists from industry and academia
to discuss potential interesting directions for research for both hybrid
systems and emerging semantics.

The deadline for submissions has been extended to *August 6th*.

*Short and long papers *are solicited for the following set of *non-exhaustive
*topics:
Theory, Algorithms and Methods: • Emerging semantic models e.g.,
distributional semantics, onto-distributional and other non-declarative or
pseudo-declarative semantics
• Synergies between emerging and ontological semantics e.g., using semantic
data and technologies to explain or improve distributional models, using
distributional approaches to acquire knowledge bases
• Foundational proposals for content models that combine statistical and
symbolic representations
• Novel embedding algorithms, especially for diverse data such as knowledge
graphs, RDF, and ontologies
• Statistical machine learning methods and algorithms for symbolic
representations Applications

• Creating symbolic representations from machine learning
• Web search
• Question answering
• Personalization
• Data Mining
• User interfaces and visualization
• Semantic recommendations
• Link prediction
• Node classification
• Instance matching/Entity resolution
• Knowledge graph embeddings
• Knowledge graph completion
Experiments, Systems and Data


• Novel datasets, especially datasets acquired through, or useful for
evaluating, hybrid approaches
• Novel methodologies, concerning both evaluations and data
curation/collection
• Experimental results using existing methods, including negative results
of interest
• Systems issues in hybrid systems, including best practices, case studies,
lessons learned, and feature descriptions

We will also accept a small number of *vision, opinion and position papers
that provide discussions on challenges and roadmaps (for hybrid systems,
and emerging semantic models). *

All papers should be formatted according to the standard LNCS Style
<http://www.springer.com/us/computer-science/lncs/conference-proceedings-guidelines>.
All papers will be peer reviewed, single-blinded. Authors whose papers are
accepted to the workshop will have the opportunity to participate in a
poster session, and some set may also be chosen for oral presentation. Long
papers should not exceed than 12 pages, and short papers should not exceed
6 pages, including all references. The accepted papers will be published
online and will not be considered archival. Proceedings will be available
for download after the conference.

All papers will be peer reviewed, single-blinded. Authors whose papers are
accepted to the workshop will have the opportunity to participate in a
poster session, and some set may also be chosen for oral presentation. Long
papers should not exceed than 12 pages, and short papers should not exceed
6 pages, including all references. The accepted papers will be published
online and will not be considered archival. Proceedings will be available
for download after the conference.

We are using the EasyChair system for submissions. Please upload your
submissions to our EasyChair submission
<https://easychair.org/conferences/?conf=hssues2017> system.

*Organization:*

Xin Dong, Amazon

R.V. Guha, schema.org

Pascal Hitzler, Wright State University,

Mayank Kejriwal, USC/ISI

Freddy Lecue, Accenture

D. Sivakumar, Google

Pedro Szekely, USC/ISI

Michael Witbrock, IBM


Please email any inquiries to kejriwal@isi.edu

Best regards,

*Mayank Kejriwal*
*USC/ISI*