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Data Science for Retail and E-commerce workshop (colocated with SIAM SDM 20)

DSRE 2020

URL: https://sdm-dsre.github.io/
Event Date: 2020-05-09 ~ 2020-05-09
Submission Date: 2020-02-15
Location: Cincinnati, United States of America

Data Mining & Analysis Databases & Information Systems

Data Science for Retail and E-commerce (DSRE) workshop
Saturday, 9th May 2020
Website: https://sdm-dsre.github.io/
Co-located with SIAM International Conference on Data Mining (SDM20)
https://www.siam.org/conferences/cm/conference/sdm20
====Description====
Retail is the sale of goods and services from a brick-and-mortar business to a consumer for their own use. E-commerce refers to the sale of goods and services via commercial transactions made electronically over the internet. Omnichannel retailing integrates both brick-and-mortar and e-commerce sales channels to provide consumers a flexible retail shopping experience. Global retail sales were US$18.84 trillion of which e-commerce sales accounted for US$ 2.86 trillion representing 15.2% web penetration. Similar to other industries, there has been a growing interest in leveraging data science and related techniques in retail and e-commerce (Retail E-com) to provide a more efficient, convenient and personalized shopping experiences to increase customer foot traffic and spend. With the democratization of machine learning and artificial intelligence, there is a great opportunity to bring awareness of Retail E-com to more experts in the SDM community and tackle problems which can have a wide impact in this multi trillion-dollar industry. There are plenty of opportunities to apply data science in the customer retail journey ranging from pre-interaction marketing, product search and recommendations and inventory management, to warehouse operations automation, delivery prediction and customer aftercare.
We expect our workshop will not only expose current researchers in SDM community to unexplored high impact problems in e-commerce, but also help grow the community by attracting researchers from the broader retail and e-commerce space.
This workshop welcomes submissions from both researchers and industry practitioners in Retail e-com. We solicit research works that are broadly related to data science on retail and e-commerce data, including data cleaning, data normalization, classification, clustering, predictive analytics, optimization techniques, and ranking. Submissions are solicited in the form of research papers which propose new techniques and advances using data mining techniques for Retail e-com, as well as industry papers that describe practical applications and system innovations in Retail e-com application areas. Case studies, works-in-progress and position and opinion papers are also welcome.
====Important dates====
Submissions Due - February 15, 2020 (11: 59 P.M. AoE)
Notification - March 15, 2020
SDM pre-registration deadline: - April 2, 2020
Camera ready: - April 15, 2020
SDM DSRE Full day Workshop - May 9, 2020
====Topics of interest (but not restricted to)====
Product Search for e-commerce
Recommender systems for e-commerce
Product Knowledge Graphs
Ontology mining for product graph construction
Personalization & contextualization for ecommerce
Product Question Answering
Voice IVR and call routing for call center operations
Shopping assistants, agents, and chat bots
Sentiment analysis and opinion mining in user-generated content
Customer Lifetime Value (CLV) prediction
Personalized marketing
Demand Prediction
Assortment optimization
Price optimization
Optimized route planning
Delivery Prediction
Reviews and sentiment analysis
Fraud and spam detection
Relevant resources and datasets
====Submission instructions====
All papers should have a maximum length of nine pages (single-spaced, two column, 10 point font, and at least 1" margin on each side). Authors should use US Letter (8.5" x 11") paper size. Long papers are limited to 9 pages (including references) and short papers are limited to 6 pages (including references). Papers must have an abstract with a maximum of 300 words and a keyword list with no more than six keywords. Authors are required to submit their papers electronically in PDF format.
Papers must be prepared in LaTeX2e, and formatted using SIAM’s macro. The macro is available at https://www.siam.org/Conferences/About-SIAM-Conferences/Proceedings#Macro
The filename is soda2e_061418.zip (LaTeX2e). Make sure you use the SIAM macro; papers prepared using other macros will not be accepted.
Submissions must describe work that is not previously published, not accepted for publication elsewhere, and not currently under review elsewhere. All submissions must be in English. Please note that at least one of the authors of each accepted paper must register for the workshop and present the paper in-person.
====Organizers====
Parikshit Sondhi (Snap)
Faizan Javed (Home Depot)
Mohammad Al Hasan (IUPUI)
Mohit Sharma (Google)
B. Aditya Prakash (Virginia Tech)
Contact: sdm-dsre@googlegroups.com

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Data Science for Retail and E-commerce workshop (colocated with SIAM SDM 20)

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