Knowledge Management in e-Commerce


April 23: 8:50 AM- 6:00 PM CET

Will be held in conjunction with the Web Conference 2021

The global e-Commerce market size is valued at USD 9.09 trillion with an annual growth rate of 14.7%. The 2020 pandemic dramatically changed people's lifestyles. E-Commerce will further accelerate its growth and penetration into people's daily lives. E-Commerce websites and apps are among the top visits of everyone's daily routine. Customers want E-Commerce websites and apps as their personal assistant that finds the exact products they are searching for, provides recommendations when they are not sure which products to buy, and answers questions about product details. Extracting structural knowledge about e-Commerce products from their text descriptions, images, reviews, customer interaction logs is the key for building delightful shopping experience for search, recommendation, advertising, and product QA. Many challenges in building a product knowledge base can benefit from the learnings of building a semantic web. On the other hand, the unique data in e-commerce can spike new research directions in the web conference community. The KMEcommerce workshop aims to bring together researchers from both academia and industry labs to exchange notes and get a pulse for the state of art of improving e-commerce customer experience with product knowledge mining and management.

Organization

Chair

  • Bing Yin
    Amazon
  • Luna Xin Dong
    Amazon
  • Haixun Wang
    Instacart
  • Chao Zhang
    GaTech

Program Committee

To Be Announced Soon

Key Dates


12/21/2020: Submissions open
2/28/2021: Workshop papers due
3/15/2021: Notification of accepted papers
4/24/2021: Workshop Day

Confirmed Keynote Speakers and Panelists

To Be Announced Soon

Call For Papers

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
• Advertising
• 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).

Submission Directions

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: https://www.acm.org/publications/proceedings-template.

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 alexbyin@amazon.com