Amit Somech

According to our database, Amit Somech authored at least 30 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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., August, 2024

Generating Tables from the Parametric Knowledge of Language Models.

Yevgeni Berkovitch, Oren Glickman, Amit Somech, Tomer Wolfson

CoRR, 2024

LINX: A Language Driven Generative System for Goal-Oriented Automated Data Exploration.

Tavor Lipman, Tova Milo, Amit Somech, Tomer Wolfson, Oz Zafar

CoRR, 2024

2023

ATENA-PRO: Generating Personalized Exploration Notebooks with Constrained Reinforcement Learning.

Tavor Lipman, Tova Milo, Amit Somech

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

Selecting Sub-tables for Data Exploration.

Yael Amsterdamer, Susan B. Davidson, Tova Milo, Kathy Razmadze, Amit Somech

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Cluster-Explorer: An interactive Framework for Explaining Black-Box Clustering Results.

Sariel Tutay, Amit Somech

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

EFFECTS: Explorable and Explainable Feature Extraction Framework for Multivariate Time-Series Classification.

Ido Ikar, Amit Somech

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

SubStrat: A Subset-Based Optimization Strategy for Faster AutoML.

Teddy Lazebnik, Amit Somech, Abraham Itzhak Weinberg

Proc. VLDB Endow., 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 Strategy for Faster AutoML.

Teddy Lazebnik, Amit Somech, Abraham Itzhak Weinberg

CoRR, 2022

SubTab: Data Exploration with Informative Sub-Tables.

Kathy Razmadze, Yael Amsterdamer, Amit Somech, Susan B. Davidson, Tova Milo

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Demonstrating SubStrat: A Subset-Based Strategy for Faster AutoML on Large Datasets.

Teddy Lazebnik, Amit Somech

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2020

A Context-Sensitive Framework for Data Analysis

Amit Somech

PhD thesis, 2020

ExplainED: Explanations for EDA Notebooks.

Daniel Deutch, Amir Gilad, Tova Milo, Amit Somech

Proc. VLDB Endow., 2020

Automating Exploratory Data Analysis via Machine Learning: An Overview.

Tova Milo, Amit Somech

Proceedings of the 2020 International Conference on Management of Data, 2020

Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning.

Ori Bar El, Tova Milo, Amit Somech

Proceedings of the 2020 International Conference on Management of Data, 2020

Incremental Based Framework for Efficient Top-K Similarity Search in Interactive Data Analysis Sessions.

Amit Somech, Tova Milo, Oded Elbaz

Proceedings of the 23rd International Conference on Extending Database Technology, 2020

Towards Autonomous, Hands-Free Data Exploration.

Ori Bar El, Tova Milo, Amit Somech

Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019

SimMeme: A Search Engine for Internet Memes.

Tova Milo, Amit Somech, Brit Youngmann

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Boosting SimRank with Semantics.

Brit Youngmann, Tova Milo, Amit Somech

Proceedings of the Advances in Database Technology, 2019

Predicting "What is Interesting" by Mining Interactive-Data-Analysis Session Logs.

Amit Somech, Tova Milo, Chai Ozeri

Proceedings of the Advances in Database Technology, 2019

ATENA: An Autonomous System for Data Exploration Based on Deep Reinforcement Learning.

Ori Bar El, Tova Milo, Amit Somech

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Declarative User Selection with Soft Constraints.

Yael Amsterdamer, Tova Milo, Amit Somech, Brit Youngmann

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Deep Reinforcement-Learning Framework for Exploratory Data Analysis.

Tova Milo, Amit Somech

Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2018

Next-Step Suggestions for Modern Interactive Data Analysis Platforms.

Tova Milo, Amit Somech

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2016

December: A Declarative Tool for Crowd Member Selection.

Yael Amsterdamer, Tova Milo, Amit Somech, Brit Youngmann

Proc. VLDB Endow., 2016

REACT: Context-Sensitive Recommendations for Data Analysis.

Tova Milo, Amit Somech

Proceedings of the 2016 International Conference on Management of Data, 2016

2015

Managing General and Individual Knowledge in Crowd Mining Applications.

Yael Amsterdamer, Susan B. Davidson, Anna Kukliansky, Tova Milo, Slava Novgorodov, Amit Somech

Proceedings of the Seventh Biennial Conference on Innovative Data Systems Research, 2015

2014

Ontology Assisted Crowd Mining.

Yael Amsterdamer, Susan B. Davidson, Tova Milo, Slava Novgorodov, Amit Somech

Proc. VLDB Endow., 2014

OASSIS: query driven crowd mining.

Yael Amsterdamer, Susan B. Davidson, Tova Milo, Slava Novgorodov, Amit Somech

Proceedings of the International Conference on Management of Data, 2014