Research

About us

The Applied Research group at eBay Israel R&D center explores and provides solutions for deeply complex problems by conducting research in areas of Data Science, Machine Learning, NLP, Recommendation Systems, Information Retrieval, and Computer Vision. We work closely with the engineering and product teams to bring state of the art technology to production environments. The group focuses on a variety of topics, all with a deep impact on eBay’s core business. For example, using ML to make eBay’s data more structured, generating high quality content for eBay’s catalog, offering intelligent pricing suggestions, and guiding sellers on how to bid on eBay’s promoted listings.

Our researchers are owning the full lifecycle of their products: from understanding the business problem, through conducting the research and finding the right ML approach, to production deployment. Think, full-stack researcher / data scientist. Moreover, we see great importance in publishing our work in scientific top-tier conferences (WWW, WSDM, SIGIR, CIKM, EMNLP, IJCAI, SIGMOD, VLDB and others).

Our team closely collaborates with leading Israeli universities:

The Technion, Tel Aviv University, The Hebrew University of Jerusalem,

and Ben-Gurion University of the Negev.

Meet the team

Publications

Demonstrating TabEE: Tabular Embedding Explanations [link] 

Copul, R., Frost, N., Milo, T., & Razmadze, K.

Proceedings of the VLDB Endowment17(12), 4285-4288

CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers [link] 

Ben-Tov, Matan, Daniel Deutch, Nave Frost, and Mahmood Sharif

IEEE Symposium on Security and Privacy (SP) 2024, pp. 227-227. IEEE Computer Society, 2024

Predicting Fact Contributions from Query Logs with Machine Learning. [link] 

Arad, Dana, Daniel Deutch, and Nave Frost

EDBT, pp. 704-716. 2024

Evaluating Anomaly Explanations Using Ground Truth [link] 

Antwarg Friedman, Liat, Chen Galed, Lior Rokach, and Bracha Shapira

AI 5, no. 4 (2024): 2375-2392

Personalized Ordering of Recommendation-Modules on an E-Commerce Homepage [link] 

Roitman, Haggai, Alex Nus, and Yotam Eshel

Companion Proceedings of the ACM on Web Conference 2024, pp. 879-882. 2024

Partially Interpretable Models with Guarantees on Coverage and Accuracy [link] 

Frost, Nave, Zachary Lipton, Yishay Mansour, and Michal Moshkovitz

International Conference on Algorithmic Learning Theory, pp. 590-613. PMLR, 2024

TabEE: Tabular Embeddings Explanations [link] 

Copul, Roni, Nave Frost, Tova Milo, and Kathy Razmadze

Proceedings of the ACM on Management of Data 2, no. 1 (2024): 1-26

Banzhaf Values for Facts in Query Answering [link] 

Abramovich, Omer, Daniel Deutch, Nave Frost, Ahmet Kara, and Dan Olteanu

Proceedings of the ACM on Management of Data 2, no. 3 (2024): 1-26

Unsupervised Search Algorithm Configuration using Query Performance Prediction [link] 

Roitman, Haggai

Companion Proceedings of the ACM on Web Conference 2024, pp. 658-661. 2024

Pricing the Nearly Known-When Semantic Similarity is Just not Enough [link] 

Fuchs, Gilad, Pavel Petrov, Ido Ben-Shaul, Matan Mandelbrod, Oded Zinman, Dmitry Basin, and Vadim Arshavsky.

eCom@ SIGIR. 2023

Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions

Ben-Shaul, Ido, Tomer Galanti, and Shai Dekel

Transactions on Machine Learning Research (2023).

the Nearly Known – When Semantic Similarity is Just not Enough

Gilad Fuchs, Pavel Petrov, Ido Ben-Shaul, Matan Mandelbrod, Oded Zinman, Dmitry Basin and Vadim Arshavski.Pricing

ECOM23@SIGIR23       

Comparative Generalization Bounds for Deep Neural Networks

Galanti, Tomer, Liane Galanti, and Ido Ben-Shaul

Transactions on Machine Learning Research (2023)

Is It Out Yet? Automatic Future Product Releases Extraction from Web Data

Fuchs, Gilad, Ido Ben-Shaul, and Matan Mandelbrod

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track. 2022

The Tip of the Buyer: Extracting Product Tips from Reviews [link] 

S Hirsch, S Novgorodov, I Guy, A Nus

ACM Transactions on Internet Technology, 2023

Lot or not: Identifying multi-quantity offerings in e-commerce [link] 

G Lavee, I Guy

ACM Transactions on Internet Technology, 2023

Promoting Tail Item Recommendations in E-Commerce [link] 

T Didi, I Guy, A Livne, A Dagan, L Rokach, B Shapira

Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization 2023

Shop by image: characterising visual search in e-commerce [link] 

A Dagan, I Guy,S Novgorodov

Information Retrieval Journal 26 (1), 2, 2023

Reverse Engineering Self-Supervised Learning

Ben-Shaul, Ido, et al

arXiv e-prints (2023): arXiv-2305

LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs

Arad, D., Deutch, D. and Frost, N.

Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 4788-4792)

Product Titles-to-Attributes As a Text-to-Text Task [link] 

Gilad Fuchs, Yoni Acriche

Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5). 2022

Third-party testing platform [link] 

Gilad Fuchs

GE Fuchs – US Patent App. 18/089,820, 2023

Automatic image selection for online product catalogs [link] 

Arnon Dagan,Ido Guy,Alexander Nus,Raphael Bryl,Noa Shimoni Barzilai, Avinoam OmerY, an Radovilsky, Einav Itamar, Gadi Mikles

US Patent 11,699,101, 2023

Query modality recommendation for e-commerce search [link] 

A Dagan, S Novgorodov, I Guy

US Patent App. 17/569,876, 2023

System, method, and medium to select a product title [link] 

A Dagan, A Zhicharevich

US Patent 11,580,589 2023

Visual quality performance predictors [link] 

I Guy, S Novgorodov, A Dagan

US Patent App. 17/448,083, 2023

Visual facet search engine [link] 

A Dagan, I Guy, V Novgorodov

US Patent App. 17/399,546, 2023

Is It Out Yet? Automatic Future Product Releases Extraction from Web Data [link] 

Fuchs, Gilad, Ido Ben-Shaul, and Matan Mandelbrod.

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track. 2022

LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs [link] 

Arad, D., Deutch, D. and Frost, N., 2022, October.

Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 4788-4792).

Product Titles-to-Attributes As a Text-to-Text Task [link] 

Gilad Fuchs, Yoni Acriche

Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5). 2022

An Image is Worth a Thousand Terms? Analysis of Visual E-Commerce Search
Arnon Dagan, Ido Guy, Slava
Novgorodov
SIGIR 2021 – July 2021, Montreal, Canada
PreSizE: Predicting Size in E-Commerce using TransformersA
Yotam Eshel, Or Levi, Haggai
Roitman, alexander Nus
SIGIR 2021 – July 2021, Montreal, Canada
Automatic Form Filling with Form-Bert
 
Gilad Fuchs, Haggai Roitman, Matan Mandelbrod: 
SIGIR 2021 – July 2021, Montreal, Canada, 2021
Improving Constrained Search Results By Data Melioration 
Ido Guy, Tova Milo, Slava 
Novgorodov, Brit Youngmann
ICDE’ 21 April 2021 , Chania,
Greece
ConCaT: Construction of Category Trees from Search Queries in ECommerce
 
Uri Avron, Shay Gershtein, Ido Guy, Tova Milo, Slava Novgorodov

ICDE’ 21 April 2021 , Chania, Greece

Category Recognition in E-Commerce using Sequence-to-Sequence Hierarchical Classification 
Idan Hasson, Slava Novgorodov, Gilad Fuchs, Yoni Acriche
WSDM’21 – March 2021, Jerusalem, Israel
Generating Tips from Product Reviews
 
Sharon Hirsch, Slava Novgorodov, Ido Guy, Alexander Nus
WSDM’21 – March 2021, Jerusalem, Israel
Event-driven Query      Expansion 
 
 
Guy Rosin, Ido Guy, Kira 
Radinsky
WSDM’21 – March 2021, Jerusalem, Israel
Descriptions from the Customers: Comparative Analysis of Review-based Product Description Generation Methods
Slava Novgorodov, Ido Guy, Guy Elad, Kira Radinsky
ACM Transactions on Internet Technology, Vol. 20, Issue 4, Article 44 (October 2020)
Intent-Driven Similarity in E-Commerce Listings
 
 
 
Gilad Fuchs, Yoni Acriche, Idan Hass  on, Pavel Petrov
CIKM’20 – October 2020, Galway, Ireland
 
E-Commerce Dispute Resolution Prediction
 
 
David Tsurel, Michael Doron, Alexander Nus, Arnon Dagan, Ido Guy, Dafna Shahaf
CIKM’20 – October 2020, Galway, Ireland
 
tdGraphEmbed: Temporal Dynamic Graph-Level Embedding
 
Moran Beladev, Lior Rokach, Gilad Katz, Ido Guy, Kira Radinsky
CIKM’20 – October 2020, Galway, Ireland
 
 
CONCIERGE: Improving Constrained Search Results by Data Melioration
Ido Guy, Tova Milo, Slava Novgorodov, Brit Youngmann

VLDB’20 – August 2020, Tokyo, Japan

Product Bundle Identification using Semi-Supervised Learning
Hen Tzaban, Ido Guy, Asnat Greenstein-Messica, Arnon Dagan, Lior Rokach, Bracha Shapira
SIGIR’20 – July 2020, Xi’an, China
Query Reformulation in E-Commerce Search
 
Sharon Hirsch, Ido Guy, Alexander Nus, Arnon Dagan, Oren Kurland
SIGIR’20 – July 2020, Xi’an, China
MC3: A System for Minimization of Classifier Construction Cost
Shay Gershtein, Tova Milo, Gefen Morami, Slava Novgorodov
SIGMOD’20 – June 2020, Portland, Oregon, USA
 
Minimization of Classifier Construction Cost for Search Queries
 

 

Shay Gershtein, Tova Milo, Gefen Morami, Slava Novgorodov
SIGMOD’20 – June 2020, Portland, Oregon, USA
Inventory Reduction via Maximal Coverage in E-Commerce
 
 
 
Shay Gershtein, Tova Milo, Slava Novgorodov
EDBT’20 – March 2020, Copenhagen, Denmark
Cross-Cultural Transfer Learning for Text Classification 
 
 
 
Dor Ringel, Gal Lavee, Ido Guy, Kira Radinsky
EMNLP’19 – November 2019, Hong Kong, China
Learning to Generate Personalized Product Descriptions
 
 
Guy Elad, Ido Guy, Slava Novgorodov, Benny Kimelfeld, Kira Radinsky
CIKM’19 – November 2019, Beijing, China
ReducE-Comm: Effective Inventory Reduction System for E-Commerce
Shay Gershtein, Tova Milo, Slava Novgorodov
CIKM’19 – November 2019, Beijing, China
Node Embedding over  Temporal Graphs

Uriel Singer, Ido Guy, Kira 
Radinsky
IJCAI’19 – August 2019, Macao, 
China
Generating Product Descriptions from User  Reviews 
Slava Novgorodov, Ido Guy, Guy Elad, Kira Radinsky
The Web Conference ’19 – May 2019, San Francisco, California, USA
Query Driven Data Labeling with Experts: Why Pay Twice?
 
Eyal Dushkin, Shay Gershtein, Tova Milo, Slava Novgorodov
EDBT’19 – March 2019, Lisbon, 
Portugal
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