Call For Papers
SIGIR eCom is a full day workshop taking place on Thursday, July 25, 2019 in conjunction with SIGIR 2019 in Paris, France.
Important Dates
- Submissions Due - May 17, 2019 (11: 59 P.M. AoE)
- Notification - May 31, 2019
- Camera Ready Version of Papers Due - June 14, 2019
- SIGIR eCom Full day Workshop - July 25, 2019
We invite quality research contributions, position and opinion papers addressing relevant challenges in the domain of eCommerce. We invite submission of papers and posters of two to ten pages (including references), representing original research, preliminary research results, proposals for new work, position and opinion papers. All submitted papers and posters will be single-blind and will be peer reviewed by an international program committee of researchers of high repute. Accepted submissions will be presented at the workshop.
Topics
Topics of interest include, but are not limited to:
- Machine learning techniques such as online learning and deep learning for eCommerce applications
- Semantic representation for users, products and services & Semantic understanding of queries
- Structured data and faceted search, for example, converting unstructured data to its structured form
- The use of domain specific facets in search and other IR tasks, and how those facets are chosen
- Query intent, suggestion, and auto-completion
- Temporal dynamics for Search and Recommendation
- Models for relevance and ranking for multi-faceted entities
- Recall-oriented search for eCommerce including deterministic sorting of results lists (e.g. price low to high)
- Click models for eCommerce domain
- Session aware, and session oriented search and recommendation
- Construction and use of knowledge graphs, and ontologies for search and recommendations
- Personalization & contextualization, and the use of personal facets such as age, gender, location etc.
- Indexing and search in a rapidly changing environment (for example, an auction site)
- Efficiency and scalability
- Diversity in product search and recommendations
- Strategies for resolving extremely low (or no) recall queries
- The use of external features such as reviews and ratings in ranking
- User interfaces (mobile, desktop, voice, etc.) and personalization
- Reviews and sentiment analysis
- The use of social signals in ranking and beyond
- Performance metrics and evaluation; tying lab metrics to business metrics and KPIs
- The balance between business requirements and user requirements (revenue vs relevance)
- Trust and security
- Live experimentation
- Questions and answering, chat bots for eCommerce
- Cross-Lingual search and machine translation
- Fashion eCommerce
- Conversational commerce: shopping using voice assistants such as Amazon Alexa and Google Now
- Resources and data sets
Data/ Resource Track
In order to promote academic research in the eCommerce domain, we plan to accept a small number of high quality dataset contributions. These submissions should be accompanied by a clear and detailed description of the dataset, some potential questions and applications that arise from it. Preliminary empirical investigations conveying any insight about the data will increase the quality of the submission.
