Workshop on Automatic Creation and Curation of Knowledge Bases (WACCK-2014) at SIGMOD

June 27, 2014, Snowbird, Utah, USA

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

Invited Speakers

  • Luna Dong (Google)
  • Lise Getoor (University of California at Santa Cruz)
  • Oktie Hassanzadeh (IBM Research) 
  • Benny Kimelfeld (LogicBlox)
  • Olivier Lichtarge (Baylor College of Medicine)
  • Partha Talukdar (CMU) 
  • Daisy Zhe Wang (University of Florida)

Accepted Papers (Oral presentation)

  • Tomasz Tylenda, Yafang Wang and Gerhard Weikum. Spotting Facts in the Wild
  • Arvind Neelakantan, Alexandre Passos and Andrew McCallum. A Hierarchical Model for Universal Schema based Relation Extraction