Connectionists: CIKM 2020 - Call for Research Papers - COVID19 UPDATES

[CIKM 2020 Publicity]

**IMPORTANT ANNOUNCEMENT**

This year, CIKM 2020 will become a fully VIRTUAL CONFERENCE, with reduced
fees, no travel involved, and presentations given via pre-recorded videos,
followed by synchronized online discussions during the scheduled conference
period.

To reflect this change, submission deadlines have been revised (see below).

** CALL FOR FULL AND SHORT RESEARCH  PAPERS **

29th ACM International Conference on Information and Knowledge Management (CIKM
2020)

Galway, Ireland, Oct. 19th-23rd, 2020

https://cikm2020.org/call-for-papers
<https://cikm2020.org/call-for-papers-full-and-short-research-papers/>

2020 Theme: Data and knowledge for the next generation: sustainability,
transparency and fairness

The Conference on Information and Knowledge Management (CIKM) is a key
event for the international academic, business and government communities
to discuss research on information retrieval, data science, and knowledge
management. CIKM is uniquely situated to highlight technologies and
insights that materialize the big data and artificial intelligence vision
of the future.

Full and Short Research Papers
NEW IMPORTANT DATES

Full and Short Paper Abstract Submission Deadline: May 8, 2020

Full and Short Paper Submission Deadline: May 15, 2020

Full and Short Paper Acceptance Notification: July 17, 2020

Full and Short Research Paper Camera Ready Submission Deadline: August 17,
2020

 Anywhere on Earth time

Topics of Interest

We encourage submissions of high-quality research papers on all topics in
the general areas of artificial intelligence, databases, information
retrieval, and knowledge management. Topics of interest include, but are
not limited to, the following areas:

   -

   Data and information acquisition and preprocessing (e.g., data crawling,
   data quality, data privacy, mitigating biases, and data wrangling)
   -

   Integration and aggregation (e.g., semantic processing, data provenance,
   data linkage, data fusion, (knowledge) graphs, data warehousing, privacy
   and security, modelling, information credibility)
   -

   Efficient data processing (e.g., serverless, data-intensive computing,
   database systems, indexing and compression, architectures, distributed data
   systems, dataspaces, customised hardware)
   -

   Analytics and machine learning (e.g., OLAP, data mining, machine
   learning and AI, scalable analysis algorithms, algorithmic biases, event
   detection and tracking, understanding, and interpretability)
   -

   Neural Information and knowledge processing (e.g. graph neural networks,
   domain adaptation, transfer learning, network architectures, neural
   ranking, neural recommendation, and neural prediction)
   -

   Information access and retrieval (e.g., facets and entities, web search,
   question answering, and dialogue systems, retrieval models, query
   processing, personalization, recommender and filtering systems)
   -

   Special data processing (e.g., multilingual text, sequential, stream,
   spatio-temporal, (knowledge) graph, multimedia, scientific, and social
   media data)
   -

   Understanding multi-modal content (e.g., natural language processing,
   speech recognition, computer vision, content understanding, knowledge
   extraction, knowledge graphs, and knowledge representations)
   -

   Data presentation (e.g., visualization, summarization, readability,
   understandability, transparency, VR, speech input and output)
   -

   Users and interfaces for information and data systems (e.g., user
   behaviour analysis, user interface design, perception of biases,
   personalization, interactive information retrieval, interactive analysis,
   spoken interfaces)
   -

   Crowdsourcing (e.g. task assignment, worker reliability, optimisation,
   trustworthiness, transparency, best practices)
   -

   Comparative evaluation, performance studies, and benchmarks (e.g.,
   online and offline evaluation, best practices)

Check our sponsorship options <https://cikm2020.org/sponsorship/> for an
opportunity to reach out to the experts in the domain!
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