K-CAP deadline extension - abstracts due 16 September, full papers 21 September

*apologies for cross-posting*



¡ Given the high number of requests the deadline is extended to 21
September 2021 but you *MUST* submit an abstract by 16 September so
reviewers can be assigned !


K-CAP 2021
The Eleventh International Conference on Knowledge Capture
December 2 - 3, 2021
A virtual conference
https://www.k-cap.org/2021/


*Call for Papers*
The massive quantity and increasing availability of information on the Web
have catalyzed research in a wide range of fields. Today's data-driven
world, however, needs more than an abundance of information, and there is a
broadening focus on information quality and accuracy. Given the increasing
demand for higher quality, accurate information that can be effectively and
unambiguously used, the study of precise and scalable knowledge capture is
of crucial importance. Knowledge capture involves the extraction of useful
knowledge from multiple, potentially heterogeneous sources, as well as its
acquisition directly from human experts.

The International Conference on Knowledge Capture, K-CAP, is a forum that
brings together members of disparate research communities who are
interested in efficiently and precisely capturing knowledge from a variety
of heterogeneous sources, and in creating representations that can be
useful for automated reasoning, analysis, and other forms of machine
processing, as well as to support users in knowledge-intensive
collaborative tasks.

To discuss and advance the goals of scalable and precise knowledge capture,
K-CAP 2021 aims to attract researchers from diverse areas of artificial
intelligence, including knowledge representation and reasoning, knowledge
acquisition, semantic web, intelligent user interfaces for knowledge
acquisition and retrieval, query processing and question answering over
heterogeneous knowledge bases, novel evaluation paradigms, problem-solving
and reasoning, agents, information extraction from structured or
unstructured data, machine learning and representation learning,
information enrichment and visualization, as well as researchers interested
in cyber-infrastructures to foster the publication, retrieval, reuse, and
integration of data.

*Topics of interest*

    - Knowledge acquisition
    - Knowledge authoring
    - Knowledge extraction
    - Knowledge management
    - Knowledge publication
    - Knowledge capture from multimodal data, e.g., text, audio, visual
    - Knowledge capture for the Semantic Web and the Web of Linked Data
    - Knowledge capture and enrichment in specific domains such as earth
and life sciences
    - Knowledge capture and Interoperability with existing Knowledge Graphs
(e.g., Wikidata, DBpedia)
    - Entity linking and resolution using target Knowledge (e.g. Wikidata,
DBpedia)
    - Collaborative and social approaches to knowledge management and
acquisition
    - Crowdsourcing for knowledge capture and refinement
    - Handling bias in knowledge capture
    - Knowledge capture from social environments and contexts
    - Problem-solving knowledge and methods
    - Knowledge-based markup techniques
    - Modeling methodologies for ontologies and knowledge graphs
    - Narrative intelligence
    - Knowledge capture through storytelling
    - Provenance and trust issues in knowledge intensive systems
    - Services and applications that enable or utilize data capture
techniques
    - Semantic search and query enrichment
    - Knowledge engineering and knowledge governance
    - Ontology design patterns
    - Similarity measurement and analogy-based reasoning
    - Extracting knowledge graphs from unstructured/semi-structured and
multimedia data
    - Summarization techniques for knowledge graphs
    - Visualization of knowledge graphs and visual query interfaces
    - Services and API for knowledge graphs
    - Addressing scalability issues for distributed knowledge graphs
    - Automated construction, enrichment and cleaning of knowledge graphs
and alignment to existing graphs
    - Hybrid approaches for knowledge capture combining knowledge
engineering and machine learning
    - Data dynamicity, heterogeneity, and decay in knowledge intensive
systems

*Submissions*

The eleventh International Conference on Knowledge Capture, K-CAP 2021,
features a full papers track for research papers, as well as tracks for
short papers, for visionary ideas, and for demos.

- Full papers, which describe original research, can be up to 8 pages long
including references. Full papers will appear in the conference proceedings
and will be citable as K-CAP 2021 publications;
- Short papers, which may describe (possibly preliminary or open-ended)
research, applications (academic, industrial or otherwise), and late
breaking results, can be up to 4 pages long, including references. Short
papers will also appear in the conference proceedings and will be citable
as K-CAP 2021 publications;
- Visionary papers, which describe outrageous ideas or potentially
preliminary, but highly innovative research, can be up to 2 pages long,
including references. Visionary papers will be presented as short talks in
the conference program;
- Demo papers, which exemplify applications or illustrate work presented in
other submissions, can be up to 4 pages long, including references. Demos
will be presented as short talks in the conference program.

Authors of all paper types will present their work in plenary sessions
during the conference. Presentation timing for the different types of
papers will be announced once the program is crafted.

K-CAP is not a double-blind conference, hence authors should list their
names and affiliations on the submission. Please use the ACM 2 column SIG
Conference Proceedings template for your submission. Submissions in HTML
format are welcome, so long as authors of HTML submissions also provide a
conversion of their submission to a PDF file that adheres to the required
ACM template for proceedings. Papers submitted to the main conference track
should not have been published before in an archival venue, or currently be
under review in an archival venue. Authors are welcome to submit papers
that have been published as a preprint on arXiv, or in a non-archival venue
like a workshop.

All submissions to K-CAP should be made through EasyChair:
https://easychair.org/conferences/?conf=kcap21

This year we will embrace the FAIR principles by collecting structured
metadata of the datasets, software, ontologies and methods generated by
K-CAP submissions. Authors will be encouraged to add these resources in the
EasyChair submission form (together with a brief description). Accepted
papers with resources will be highlighted in the main K-CAP conference page.

*Important Dates*
  - Abstract submission: September 16, 2021
  - Paper submission: September 21, 2021
  - Author notification: October 13, 2021
  - Camera ready version due: October 25, 2021
  - Conference dates: December 2-3, 2021

All deadlines are midnight AoE (Anywhere on Earth).