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活动简介

The huge and rapidly increasing amount of structured and unstructured data available on the Web makes it both possible and necessary to support users in finding relevant information. The trend moves more and more towards smart knowledge services that are able to find information, aggregate them, draw inferences, and present succinct answers without requiring the user to wade through a large number of documents. The novel avenues made possible by knowledge services are numerous and diverse, including ubiquitous information access (from smartphones, tablets, smart watches, etc.), barrier-free access to data (especially for the blind and disabled) and knowledge discovery.

Over the last years, several challenges and calls for research projects have pointed out the dire need for pushing natural language interfaces. In this context, the importance of Semantic Web data as a premier knowledge source is rapidly increasing. But we are still far from having accurate natural language interfaces that allow handling complex information needs in a user-centric and highly performant manner. The development of such interfaces requires the collaboration of a range of different fields, including natural language processing, information extraction, knowledge base construction and population, reasoning, and question answering.

The main goal of this workshop is to join forces in the collaborative development of open frameworks for knowledge extraction and question answering, to share standards, and to foster the creation of an ecosystem of tools and benchmarks. The workshop will therefore not only comprise short and long paper presentations but also a hands-on session on already existing frameworks, standards, and benchmarking campaigns, as well as a social meet-up.

征稿信息

重要日期

2017-06-27
初稿截稿日期
2017-07-17
初稿录用日期
2017-07-24
终稿截稿日期

征稿范围

Specific topics include but are not limited to:

  • Natural Language Interface for Web of Data
    • Browsing Linked Data
    • Question Answering over Linked Data
    • Benchmarking Natural Language Interfaces
    • Term Matching and Entity Disambiguation
    • SPARQL Query Pattern Generation
    • Schema-agnostic Query Generation
    • Discovery of Linked Data Sources
    • Endpoint Profiling
    • Dealing with Data and Schema Heterogeneity
    • Providing Justifications of Answers and Conveying Trust
    • Knowledge Base Design for Question Answering
    • Language Resources and NLP Software for Question Answering
    • Reasoning for Question Answering
    • Natural Language Querying of RDF exposed as Linked Data
    • Natural Language Querying of Web Services
    • User Feedback and Interaction
    • Dialogue Systems
    • Personal Assistants
  • Knowledge Base Construction for Question Answering
    • Entity-centered Knowledge Bases
    • Event-centered Knowledge Bases
    • Human Intervention of Knowledge with QA
    • NLP Annotations for Knowledge Extraction and Machine Reading
    • Gold Standard Data Sets and Quality Assessment
    • Indexing and Mappings from Existing Sources (Structured, Semi-structured or Unstructured)
  • NLP Annotation Framework for Knowledge Base and Question Answering
    • NLP annotation framework
      • to represent the layers and their structure of language understanding in graph formats such as XML and RDF, including metadata and underlying ontologies
    • NLP annotation knowledge base
      • to access existing annotated NLP resources efficiently and effectively for further processing for knowledge base engineering and question answering
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重要日期
  • 08月11日

    2017

    会议日期

  • 06月27日 2017

    初稿截稿日期

  • 07月17日 2017

    初稿录用通知日期

  • 07月24日 2017

    终稿截稿日期

  • 08月11日 2017

    注册截止日期

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