Organizers Program Committee Program Important Dates CFP

First Content Understanding and Generation for E-commerce Workshop

KDD 2022

Call for Papers

Online experience on any e-commerce website is largely driven by the content customers interact with. The large volume of diverse content on e-commerce platforms, and the advances in machine learning provide opportunity for gathering insights from e-commerce content and build systems that can reliably generate content to improve shopper experience. The first workshop on content understanding and generation for the e-commerce aims to bring together researchers from industry and academia to discuss recent advances and challenges specific to these areas.

The workshop is a half-day event. We encourage submission of novel work-in-progress papers that show promising directions or demonstration systems, to facilitate discussion during the workshop. The workshop will solicit contributions related to the theme of supporting generation and curation of content for e-commerce which includes (but is not limited to):

  • Cold start brand/product summary or promotional video generation
  • Domain adaptation methods for understanding user submitted product review texts and images
  • Domain adaptation methods for recognition of products in non-natural datasets
  • Novel approaches to generate and evaluate product catalogue, review and comparison summaries
  • Multimodal techniques for matching image and text from product feature/advertisement videos and product description
  • Multimodal and multi-view content modelling aggregating information from multiple product data sources (including text, images, and video) to support product description or advertisement creation
  • Multimodal techniques for understanding affective expressions, including non-visual signals such as audio or speech from product videos and advertisements
  • Multimodal action/scene recognition in product feature/advertisement videos across product verticals like sports, healthcare, entertainment or lifestyle
  • Different approaches and metrics to assess the visual appeal of e-commerce content
  • Product catalogue moderation and optimization
  • Guided generative models for images, audio and videos based on product script and brand story
  • Product description or brand store layout/template generation guided by business metrics such as click through rate (CTR) or revenue
  • Generation of interpretable and actionable insights from product catalogue and user submitted reviews for content creators
  • Few shot learning approaches to bootstrap generation models for new brands, products or demographics
  • Evaluation metrics to assess the quality of generated content
  • Cold start modelling for new category or product

We solicit two types of submissions – full papers of 6 pages and short papers of at most 2 pages excluding references. The submissions should be anonymized for double blind reviews. Please omit author names or affiliations to maintain anonymity. The submissions must be in PDF format and use two-columns ACM Conference Proceeding template. Template guidelines are here. Submit your paper through the workshop CMT submission site: https://cmt3.research.microsoft.com/EcomGen2022. The accepted papers will be published on the workshop website.

Important Dates

Following are the proposed important dates for the workshop. All deadlines are due 11:59pm anywhere on earth.

Program

Five invited speakers shall talk about various topics associated with E-commerce content generation and moderation.

Aleix Martinez

Ohio State University

Lydia Chilton

Columbia University

Kristen Grauman

University of Texas at Austin

Sam Wiseman

Duke University

Jacopo Tagliabue

Coveo

Program Committee

  • Stephen Guo, Walmart Labs
  • Musen Wen, Walmart Labs
  • Djordje Gligorijevic, Ebay
  • Yuri Brovman, Ebay Ads
  • Menghan Wang, Ebay Ads
  • Wei Zhou, Ebay Ads
  • Deepalakshmi Gopinath, Ebay
  • Yichao Zhou, Google
  • Aayush Prakash, Facebook
  • Procheta Sen, UCL
  • Ganesh Jawahar, UBC
  • Kevin Yen, Yahoo! Research
  • Keqian Li, Yahoo! Research
  • Shaunak Mishra, Amazon Ads
  • Soumya Roy, Amazon Ads
  • Shilpa Ananth, Amazon Ads
  • Yashal Kanungo, Amazon Ads
  • Indraneil Paul, Amazon Ads
  • Bryan Wang, Amazon Machine Learning
  • Yang Liu, Amazon Machine Learning
  • Jinmiao Fu, Amazon Machine Learning
  • Sameer Kanase, Amazon

Organizers

  • Sumit Negi, Amazon Ads
  • Rajdeep Banerjee, Amazon Ads
  • Manisha Verma, Amazon Ads
  • Pooja A, Amazon Ads
  • Lydia Chilton, Columbia University
  • Mithun Das Gupta, Microsoft
  • Vinay P. Namboodiri, University of Bath
  • Dinesh Garg, IBM Research