AKBC 2017

6th Workshop on Automated Knowledge Base Construction (AKBC) 2017

at NIPS 2017 in Long Beach, California, December 8th, 2017.

Extracting knowledge from Web pages, and integrating it into a coherent knowledge base (KB) is a task that spans the areas of natural language processing, information extraction, information integration, databases, search, and machine learning. Recent years have seen significant advances here, both in academia and industry. Most prominently, all major search engine providers (Yahoo!, Microsoft Bing, and Google) nowadays experiment with semantic KBs. Our workshop serves as a forum for researchers on knowledge base construction in both academia and industry.

Unlike many other workshops, our workshop puts less emphasis on conventional paper submissions and presentations, but more on visionary papers and discussions. In addition, one of its unique characteristics is that it is centered on keynotes by high-profile speakers. AKBC 2010, AKBC 2012, AKBC 2013, AKBC 2014 and AKBC 2016 each had a dozen invited talks from leaders in this area from academia, industry, and government agencies. We had senior invited speakers from Google, Microsoft, Yahoo, several leading universities (MIT, Stanford, University of Washington, CMU, University of Massachusetts, and more), and DARPA. With this year’s workshop, we aim to resume this positive experience. By established researchers for keynotes, and by focusing particularly on vision paper submissions, we aim to provide a vivid forum of discussion about the field of automated knowledge base construction. The AKBC 2017 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:

  • machine learning on text; unsupervised, lightly-supervised and distantly-supervised learning; learning from naturally-available data
  • deep learning for representing knowledge bases
  • human-computer collaboration in knowledge base construction; automated population of wikis
  • inference for graphical models and structured prediction; scalable approximate inference
  • information extraction; open information extraction, named entity extraction; ontology construction
  • entity resolution, relation extraction, information integration; schema alignment; ontology alignment; monolingual alignment, alignment between knowledge bases and text
  • pattern analysis, semantic analysis of natural language, reading the web, learning by reading
  • databases; distributed information systems; probabilistic databases
  • scalable computation; distributed computation
  • question-answering using KBs, queries on mixtures of structured and unstructured data; querying under uncertainty
  • dynamic data, online/on-the-fly adaptation of knowledge
  • languages, toolkits and systems for automated knowledge base construction
  • demonstrations of existing automatically-built knowledge base

Luna Dong Amazon
Tom Mitchell Carnegie Mellon University
Maximilian Nickel Facebook AI Research
Sebastian Riedel Bloomsbury AI / University College London
Sameer Singh University of California, Irvine
Ivan Titov University of Edinburgh
Luke Zettlemoyer University of Washington/Allen Institute for Artificial Intelligence
  • Submission Due: October 21, 2017
  • Student Travel Award Application Due: October 22, 2017
  • Notification: November 5, 2017
  • Camera-ready Due: November 12, 2017
  • Workshop: December 8, 2017

Deadlines are at 11:59pm PDT, and subject to change.


For any questions, please e-mail info@akbc.ws.

Program Committee

  • Alan Akbik
  • Alan Ritter
  • Andreas Vlachos
  • Anthony Platanios
  • Arun Chaganty
  • Arvind Neelakantan
  • Derry Wijaya
  • Doug Downey
  • Estevam Hruschka
  • Eunsol Choi
  • Fabian Suchanek
  • James Fan
  • Jayant Krishnamurthy
  • Larysa Visengeriyeva
  • Luis Garraga
  • Matt Gardner
  • Nicoleta Preda
  • Niket Tandon
  • Niranjan Balasubramanian
  • Partha Talukdar
  • Pontus Stenetorp
  • Ralf Schenkel
  • Ramanathan Guha
  • Roman Klinger
  • Sebastian Krause
  • Siva Reddy
  • Steffen Staab
  • Stephen Bach
  • Victoria Lin
  • Xiang Ren
  • Xiao Ling
  • Yuhao Zhang