HSSUES 2017: Hybrid Statistical Semantic Understanding and Emerging Semantics |
Website | http://usc-isi-i2.github.io/ISWC17workshop/ |
Submission link | https://easychair.org/conferences/?conf=hssues2017 |
Abstract registration deadline | August 6, 2017 |
Submission deadline | August 6, 2017 |
Understanding the semantics of Web content is at the core of many applications, ranging from Web search, news aggregation and machine translation to personal assistant services such as Amazon Echo, Cortana, Siri, and Google Home. Presently, two different approaches apply to this task. The first approach utilizes a rich suite of information retrieval and machine learning techniques that capture meaning through powerful statistical tools like neural networks and distributional semantics (e.g., word2vec). Recently, such emerging semantic models have achieved state-of-the-art results in several predictive applications (e.g. recommendation, node classification, knowledge graph completion) relevant not just to the Semantic Web, but allied communities such as data mining and natural language processing. The second, more traditional, approach conveys meaning in a structured form through embedded data markup (using Schema.org, OGP, etc.) and ontologies, and can be further enhanced through available knowledge bases such as Freebase and DBpedia. Ontological notions of semantics play a central role in the Semantic Web community, permitting publishers and consumers of data to interact using a well-defined ontology. Such models give practitioners the powerful ability to reason about, and represent, instances in a well-defined manner. HSSUES is a full-day workshop that will explore the synergy, from perspectives of theory, application, experiments (including negative results) and vision, between both approaches, and how such synergies can be exploited to advance the state-of-the-art. We are interested in mechanisms, both theoretical and experimental, that range the spectrum of possible strategies and provide novel functionalities through hybrid approaches to statistical and symbolic understanding. The broader goal is to foster a discussion that will lead to cross-cutting ideas and collaborations at a timely moment when Semantic Web research has significantly started intersecting with the natural language processing and knowledge discovery communities.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference.
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. 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 system.
Committees
Program Committee
- Derek Doran, Wright State University
- Stefano Faralli, University of Manheim
- Evgeniy Gabrilovich, Google
- Majid Ghasemi-Gol, Information Sciences Institute/USC
- Goran Glavaš, University of Manheim
- Sabrina Kirrane, Vienna University
- Brigitte Krenn, Austrian Research Institute for Artificial Intelligence
- Steve Macbeth, Microsoft
- Andrew McCallum, University of Massachusetts, Amherst
- John McCrae, Insight Center for Data Analytics, National University of Ireland Galway
- Kevin Murphy, Google
- Vivek Raghunathan, Google
- Enrico Santus, The Hong Kong Polytechnic University
- Michael Spranger, Sony Computer Science Laboratories Inc.
- Jiewen A. Wu, Accenture
Organizing committee
- Xin Luna Dong, Amazon
- R. V. Guha, Schema.org
- Pascal Hitzler, Wright State University
- Mayank Kejriwal, Information Sciences Institute/USC
- Freddy Lecue, Accenture Technology Labs, Dublin
- D. Sivakumar, Google
- Pedro Szekely, Information Sciences Institute/USC
- Michael Witbrock, IBM
Venue
The conference will be held in the beautiful WU campus in Vienna, Austria as a full day workshop at the International Semantic Web Conference. Currently, the workshop date is set for October 21, 2017.
Contact
All questions about submissions should be emailed to Mayank Kejriwal (kejriwal@isi.edu).