The Knowledge Management in E-Commerce Workshop welcomes submissions from both researchers and industry practitioners in
knowledge discovery and applications for e-Commerce, including data
cleaning and (unsupervised/weakly supervised) learning from noisy data, representation learning and embeddings, information
extraction from text and graphs, user behavior modeling, and applications such as search, recommendation, advertising and QA.
Full paper submissions (maximum 8 pages) are solicited in the form of research papers which propose new techniques and
advances with industrial potential as well as papers from industry that describe practical applications and innovations in e-Commerce applications.
Short papers (maximum 4 pages) describing case studies or work-in-progress are also solicited. Exceptionally well-argued position papers are also welcome.
In addition to short and long papers above, we welcome extended abstracts (1-2 pages) covering topical areas of research that are appropriate for the workshop.
Authors of selected abstracts will be invited for oral presentations.
Top papers from the workshop will be selected for the June 2021 IEEE Data Engineering Bulletin Journal. See previous Journal since 1977 here: https://dblp.org/db/journals/debu/index.html
Papers are solicited for the following set of non-exhaustive topics related to knowledge extraction, management and e-Commerce:
Theory, Algorithms and Methods:
• Extracting product knowledge and constructing Knowledge Graph from structured, semi-structured and unstructured data.
• Effective integration and learning of domain specifc human knowledge and human labels.
• Novel methodologies about evaluations and data curation/collection
• Unsupervised learning, weakly supervised learning from noisy data.
• Multilingual learning.
• Large-scale user behavioral graph mining.
• Data quality assessment for large scale product Knowledge Graphs.
• Infrastructure of Knowledge Graph-centric architectures.
• Novel definitions and theories regarding knowledge mining and representations.
• Deep Learning in knowledge extraction.
• Effective use of public Knowledge Graphs in e-Commerce.
Applications powered by Product Knowledge
• Product search, including query processing, mission understanding, products retrieval, ranking, and rendering.
• Product question answering
• Product recommendation
• User interfaces and visualization
• Experimental results using existing methods, including negative results of interest
• Systems issues in knowledge management in e-Commerce such as best practices, case studies, lessons learned, and feature descriptions
Vision, Opinion and Position Papers
We will also accept a small number of vision, opinion and position papers that provide discussions on challenges and roadmaps
(for Knowledge Graph systems, applications and emerging models for e-commerce and product data).
Submissions are limited to a total of eight (8) pages, including all content and references, and must be in PDF format and formatted
according to the new Standard ACM
Conference Proceedings Template.
For LaTeX users: unzip acmart.zip, make, and use sample-sigconf.tex as a template.
Additional information about formatting and style files is available online at:
The accepted papers will be published online. Select papers may be invited to IEEE Data Engineering Bulletin Journal.
Proceedings will be available for download after the conference.
All papers will be peer reviewed, single-blinded. Authors whose papers are accepted to the workshop will have the opportunity to participate in a poster session,
and some set will be chosen for oral presentation.
We are using the EasyChair system for submissions. Please submit your paper using this link: https://easychair.org/conferences/?conf=km4ecommerce
Please email any enquiries to firstname.lastname@example.org