OASSIS: query driven crowd mining. - Yael Amsterdamer; Susan B. Davidson; Tova Milo; Slava Novgorodov; Amit Somech (SIGMOD Conference, 2014)

Ontology Assisted Crowd Mining. - Yael Amsterdamer; Susan B. Davidson; Tova Milo; Slava Novgorodov; Amit Somech (Proc. VLDB Endow., 2014)

Managing General and Individual Knowledge in Crowd Mining Applications. - Yael Amsterdamer; Susan B. Davidson; Anna Kukliansky; Tova Milo; Slava Novgorodov; Amit Somech (CIDR, 2015)

REACT: Context-Sensitive Recommendations for Data Analysis. - Tova Milo; Amit Somech (SIGMOD Conference, 2016)

December: A Declarative Tool for Crowd Member Selection. - Yael Amsterdamer; Tova Milo; Amit Somech; Brit Youngmann (Proc. VLDB Endow., 2016)

Next-Step Suggestions for Modern Interactive Data Analysis Platforms. - Tova Milo; Amit Somech (KDD, 2018)

Deep Reinforcement-Learning Framework for Exploratory Data Analysis. - Tova Milo; Amit Somech (aiDM@SIGMOD, 2018)

Declarative User Selection with Soft Constraints. - Yael Amsterdamer; Tova Milo; Amit Somech; Brit Youngmann (CIKM, 2019)

ATENA: An Autonomous System for Data Exploration Based on Deep Reinforcement Learning. - Ori Bar El; Tova Milo; Amit Somech (CIKM, 2019)

Predicting "What is Interesting" by Mining Interactive-Data-Analysis Session Logs. - Amit Somech; Tova Milo; Chai Ozeri (EDBT, 2019)

Boosting SimRank with Semantics. - Brit Youngmann; Tova Milo; Amit Somech (EDBT, 2019)

SimMeme: A Search Engine for Internet Memes. - Tova Milo; Amit Somech; Brit Youngmann (ICDE, 2019)

Towards Autonomous, Hands-Free Data Exploration. - Ori Bar El; Tova Milo; Amit Somech (CIDR, 2020)

Incremental Based Framework for Efficient Top-K Similarity Search in Interactive Data Analysis Sessions. - Amit Somech; Tova Milo; Oded Elbaz (EDBT, 2020)

Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning. - Ori Bar El; Tova Milo; Amit Somech (SIGMOD Conference, 2020)

Automating Exploratory Data Analysis via Machine Learning: An Overview. - Tova Milo; Amit Somech (SIGMOD Conference, 2020)

ExplainED: Explanations for EDA Notebooks. - Daniel Deutch; Amir Gilad; Tova Milo; Amit Somech (Proc. VLDB Endow., 2020)

A Context-Sensitive Framework for Data Analysis - Amit Somech (2020)

Demonstrating SubStrat: A Subset-Based Strategy for Faster AutoML on Large Datasets. - Teddy Lazebnik; Amit Somech (CIKM, 2022)

SubTab: Data Exploration with Informative Sub-Tables. - Kathy Razmadze; Yael Amsterdamer; Amit Somech; Susan B. Davidson; Tova Milo (SIGMOD Conference, 2022)

SubStrat: A Subset-Based Strategy for Faster AutoML. - Teddy Lazebnik; Amit Somech; Abraham Itzhak Weinberg (CoRR, 2022)

FEDEX: An Explainability Framework for Data Exploration Steps. - Daniel Deutch; Amir Gilad; Tova Milo; Amit Mualem; Amit Somech (Proc. VLDB Endow., 2022)

SubStrat: A Subset-Based Optimization Strategy for Faster AutoML. - Teddy Lazebnik; Amit Somech; Abraham Itzhak Weinberg (Proc. VLDB Endow., 2022)

EFFECTS: Explorable and Explainable Feature Extraction Framework for Multivariate Time-Series Classification. - Ido Ikar; Amit Somech (CIKM, 2023)

Cluster-Explorer: An interactive Framework for Explaining Black-Box Clustering Results. - Sariel Tutay; Amit Somech (CIKM, 2023)

Selecting Sub-tables for Data Exploration. - Yael Amsterdamer; Susan B. Davidson; Tova Milo; Kathy Razmadze; Amit Somech (ICDE, 2023)

ATENA-PRO: Generating Personalized Exploration Notebooks with Constrained Reinforcement Learning. - Tavor Lipman; Tova Milo; Amit Somech (SIGMOD Conference Companion, 2023)

Generating Tables from the Parametric Knowledge of Language Models. - Yevgeni Berkovitch; Oren Glickman; Amit Somech; Tomer Wolfson (CoRR, 2024)

PD-Explain: A Unified Python-native Framework for Query Explanations Over DataFrames. - Itay Elyashiv; Amir Gilad; Edna Isakov; Tal Tikochinsky; Amit Somech (Proc. VLDB Endow., 2024)

LINX: A Language Driven Generative System for Goal-Oriented Automated Data Exploration. - Tavor Lipman; Tova Milo; Amit Somech; Tomer Wolfson; Oz Zafar (EDBT, 2025)

PY-SHARQ: A Holistic Python Library for Explaining Association Rules on Relational Data. - Hadar Ben-Efraim; Susan B. Davidson; Amit Somech (SIGMOD Conference Companion, 2025)

OmniTune: A Universal Framework for Query Refinement via LLMs. - Eldar Hacohen; Yuval Moskovitch; Amit Somech (SIGMOD Conference Companion, 2025)

Explaining Black-Box Clustering Pipelines With Cluster-Explorer. - Sariel Ofek; Amit Somech (Proc. VLDB Endow., 2025)

SHARQ: Explainability Framework for Association Rules on Relational Data. - Hadar Ben-Efraim; Susan B. Davidson; Amit Somech (Proc. ACM Manag. Data, 2025)