World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
9829
World Ranking
12866
National Ranking
198

Overview

Shaul Markovitch is affiliated with the Technion - Israel Institute of Technology in Israel. Their research primarily focuses on computer science, with a significant emphasis on artificial intelligence among related subfields such as information systems, computer vision and pattern recognition, and information systems and management.

The scientist has contributed to several areas within computer science, including topic modeling, natural language processing techniques, software engineering research, explainable artificial intelligence (XAI), semantic web and ontologies, multimodal machine learning applications, and speech and dialogue systems.

Markovitch's recent papers include:

  • Concept-Based Approach to Word-Sense Disambiguation (2021), Proceedings of the AAAI Conference on Artificial Intelligence
  • Teaching Machines to Learn by Metaphors (2021), Proceedings of the AAAI Conference on Artificial Intelligence
  • Interpreting Embedding Spaces by Conceptualization (2022), arXiv (Cornell University)
  • A General Search-Based Framework for Generating Textual Counterfactual Explanations (2024), Proceedings of the AAAI Conference on Artificial Intelligence
  • Knowledge-Based Learning through Feature Generation (2020), arXiv (Cornell University)

Frequent co-authors working with Markovitch include Daniel Gilo, Ariel Raviv, Omer Levy, Adi Simhi, and Michal Badian. These collaborations have contributed to various publications across multiple venues.

Markovitch's work has been published mainly in the following venues:

  • arXiv (Cornell University) with 4 publications
  • Proceedings of the AAAI Conference on Artificial Intelligence with 3 publications

Best Publications

  • Computing semantic relatedness using Wikipedia-based explicit semantic analysis

    Evgeniy Gabrilovich;Shaul Markovitch

  • Overcoming the brittleness bottleneck using wikipedia: enhancing text categorization with encyclopedic knowledge

    Evgeniy Gabrilovich;Shaul Markovitch

  • A word at a time: computing word relatedness using temporal semantic analysis

    Kira Radinsky;Eugene Agichtein;Evgeniy Gabrilovich;Shaul Markovitch

  • Wikipedia-based semantic interpretation for natural language processing

    Evgeniy Gabrilovich;Shaul Markovitch

  • Contextual word similarity and estimation from sparse data

    Ido Dagan;Shaul Marcus;Shaul Markovitch

  • Concept-Based Information Retrieval Using Explicit Semantic Analysis

    Ofer Egozi;Shaul Markovitch;Evgeniy Gabrilovich

  • Selective Sampling for Nearest Neighbor Classifiers

    Michael Lindenbaum;Shaul Markovitch;Dmitry Rusakov

  • Feature generation for text categorization using world knowledge

    Evgeniy Gabrilovich;Shaul Markovitch

  • CONTEXTUAL WORD SIMILARITY AND ESTIMATION FROM SPARSE DATA

    Ido Dagan;Shaul Marcus;Shaul Markovitch

  • Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5

    Evgeniy Gabrilovich;Shaul Markovitch

  • Learning causality for news events prediction

    Kira Radinsky;Sagie Davidovich;Shaul Markovitch

  • The role of forgetting in learning

    Shaul Markovitch;Paul D. Scott

  • Learning models of intelligent agents

    David Carmel;Shaul Markovitch

  • Feature Generation Using General Constructor Functions

    Shaul Markovitch;Dan Rosenstein

  • Learning implicit transfer for person re-identification

    Tamar Avraham;Ilya Gurvich;Michael Lindenbaum;Shaul Markovitch

  • Opponent Modeling in Multi-Agent Systems

    David Carmel;Shaul Markovitch

  • Information filtering: selection mechanisms in learning systems

    Shaul Markovitch;Paul D. Scott

  • Parameterized generation of labeled datasets for text categorization based on a hierarchical directory

    Dmitry Davidov;Evgeniy Gabrilovich;Shaul Markovitch

  • Text categorization using external knowledge

    Evgeniy Gabrilovich;Shaul Markovitch

  • Concept-based feature generation and selection for information retrieval

    Ofer Egozi;Evgeniy Gabrilovich;Shaul Markovitch

  • Incorporating opponent models into adversary search

    David Carmel;Shaul Markovitch

Frequent Co-Authors

Evgeniy Gabrilovich
Evgeniy Gabrilovich Google (United States)
David Carmel
David Carmel Amazon (Israel)
Michael Lindenbaum
Michael Lindenbaum Technion – Israel Institute of Technology
Ehud Rivlin
Ehud Rivlin Technion – Israel Institute of Technology
Orna Grumberg
Orna Grumberg Technion – Israel Institute of Technology
Carmel Domshlak
Carmel Domshlak Technion – Israel Institute of Technology
Omer Levy
Omer Levy Deep Mind
Ido Dagan
Ido Dagan Bar-Ilan University
Yoav Goldberg
Yoav Goldberg Bar-Ilan University
Malte Helmert
Malte Helmert University of Basel

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