HQA 2019:
Second International Workshop on Hybrid Question Answering with Structured and Unstructured Knowledge

Part of K-CAP'19, 19-21 November, 2019, Marina del Rey, California, United States

CFP can be downloaded from cfp-haq19-kcap.pdf.

  • Title and abstract submission: September 25, 2019 October 6, 2019 (Anywhere on Earth)
  • Paper submission: September 27, 2019 October 6, 2019
  • Notification: October 11, 2019
  • Final version due: October 15, 2019

More and more knowledge is available electronically in a structured or unstructured form over the World Wide Web (WWW). Such knowledge has become a rich resource to answer our daily life questions and even scientific questions posed by domain experts. Accordingly, it becomes a necessity to develop tools that can (semi-)automatically answer questions based on the large amount of available data.

Such challenges have been targeted separately over the last years by different communities, including Query Answering in Semantic Web based on structured semantic data and Question Answering in Natural Language Processing based on unstructured textual data. While the former is powerful in representing complex questions and exploring background knowledge (e.g., large biomedical ontologies), it is often difficult to master and cannot be used without a specialized user interface. In contrast, the latter can formulate constraints that cannot be represented formally by query answering approaches due to the limited expressiveness of formal languages. But it is not obvious how to take into account the background and common sense knowledge to get precise answers over structured data.

The objective of this workshop is to bring together researchers and developers working on question/query answering systems over structured or unstructured knowledge, and create a platform to grow potential collaborations in this multidisciplinary task.

Topics of interest include, but are not limited to, the following:

  • Natural Language Processing based question answering
  • Ontology based query answering
  • Hybrid reasoning
  • Information extraction over unstructured and structured data
  • Applications of question answering
  • Domain-specific question answering
  • Temporal event extraction from tex
  • Temporal reasoning for query answering
  • Ontologies and knowledge graphs
  • Biomedical text analysis
  • Datasets combining structured and unstructured knowledge


Papers for the workshop should be submitted in PDF format via EasyChair https://easychair.org/conferences/?conf=hqa2019 . Submitted papers must use the new ACM format published in ACM guidelines (download from here), selecting the generic “sigconf” sample . Submissions must be in English and not exceed 4-6 pages in length.

Papers must have not been previously published or be under review at another workshop. However, we encourage submissions that present summaries or highlights of work appearing elsewhere in longer form.


PC Chairs

Organization Commmittee

  • Stefan Borgwardt, TU Dresden, Germany
  • Sanjay Kamath, LRI/LIMSI, CNRS, Université Paris Sud, France
  • Pierre Zweigenbaum, LIMSI, CNRS, Université Paris Saclay, France

Program Committe

  • Meghyn Bienvenu, CNRS, University of Bordeaux, France
  • Camille Bourgaux, ENS Paris, CNRS, France
  • Jieying Chen, LRI, CNRS, Université Paris Sud, France
  • Walter Forkel, TU Dresden, Germany
  • Guanghui Fu, Beijing University of Technology, Chine
  • Anne-Laure Ligozat, LIMSI, CNRS, Université Paris Saclay, France
  • Raghava Mutharaju, GE Global Research Center, USA
  • Fathia Sais, LRI, CNRS, Université Paris Sud, France
  • Fabian M. Suchanek, Télécom ParisTech, France
  • Michaël Thomazo, INRIA Saclay, France
  • Guohui Xiao, Free University of Bozen-Bolzano, Italy
  • Zheng Zhang, LIMSI, CNRS, Université Paris Saclay, France

Keynote speakers

We will welcome Dr. Bo Yan for an invited talk at HQA'19.

Title: Question answering methods, challenges and beyond

Abstract:The keynote will cover the general motivation of question answering systems, existing methods in utilizing unstructured and structured data for question answering, and summarize the challenges researchers are facing. In particular, it will discuss some of the ideas and models using knowledge graph embeddings for conducting conjunctive queries for complex questions. It will then provide some insights beyond textual question answering and talk about sub areas that are becoming increasingly popular, such as visual question answering and geographic question answering.

Speaker: Dr. Bo Yan

Dr. Bo Yan obtained his Ph.D. degree from the University of California, Santa Barbara. His research interests include: geospatial knowledge discovery, geospatial semantics, geo knowledge graph, geospatial entity summarization and relevance detection, spatial statistics/analytics, POI conflation, geographic information retrieval, spatial data mining, Linked Data, Semantic Web, geovisualization, and cartography. By exploiting statistical and machine learning models, he is trying to discover new patterns and solve geographic information science questions from a new perspective.


Provisional Program


For details about traveling, accommodation, and registration, please see the web pages of The K-CAP Conference