KBCOM 2018: First Workshop on Knowledge Base Construction, Reasoning and Mining
at WSDM 2018 in Los Angeles, California, Feb 9, 2018.
The 1st Workshop on Knowledge Base Construction, Reasoning and Mining (KBCOM) is a new workshop that will be co-located with WSDM 2018. The success of data mining and search technologies is largely attributed to the efficient and effective analysis of structured data. Automated construction, mining and reasoning of knowledge bases and graphs have become possible as research advances in many related areas such as information extraction, natural language processing, machine learning and databases. KBCOM aims to gather together leading experts from industry and academia to share their visions about the field, discuss latest research results, and exchange exciting ideas.
We aim to complement the main conference by trying to achieve the following goals:
Research horizons in KBCOM: The workshop focuses on invited talks from leading experts and position papers discussing forward-looking work. Its program comprises a good number of keynote speakers from both leading universities (Stanford, University of Washington and more) and industrial organizations like Amazon and Recruit Institute of Technology.
Idea exchange in KBCOM: We will organize a poster session for researchers to share ideas, collect feedback and form collaborations. We particularly encourage participants to publish new software and datasets on related topics, and will hold novel shared tasks to help develop a better community.
We expect the highlight of the workshop to be the discussions and brainstorming during invited talks and poster session. The workshop will also accept regular submissions of original research or position/visionary papers which will be presented either as highlight talks or during the poster session. With such focuses, KBCOM aims to provide a vivid forum of discussion about knowledge base-related research.
Details about the speakers and talks can be found here.
- Knowledge Base Construction:
- information extraction: named entity recognition, relation extraction, entity resolution, synonym mining;
- ontology construction; information integration; schema alignment, ontology alignment;
- tools and systems for automated knowledge base construction;
- structured prediction methods on text, sequence labeling methods on text;
- distant supervision, weak supervision techniques for text;
- Human-in-the-loop techniques for KB construction.
- Mining and Reasoning over Knowledge Bases:
- structured search, KB querying, semantic search;
- representation learning on network/graph, knowledge graph embedding, knowledge base completion/population, link prediction;
- knowledge-based systems, probabilistic knowledge bases, graph databases.
- Knowledge Base-related Applications:
- KB-based QA, hybrid QA, QA with open-domain facts;
- Injecting rule/logic into recommendation systems, recommendation with knowledge bases;
- web search using knowledge bases, search by example; User study in KB-related applications, user interface, best practices.
For any questions, please email email@example.com
We thank our sponsors for their generous support!