Michael Elhadad

4.2k total citations · 1 hit paper
73 papers, 2.3k citations indexed

About

Michael Elhadad is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michael Elhadad has authored 73 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Artificial Intelligence, 11 papers in Molecular Biology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michael Elhadad's work include Natural Language Processing Techniques (58 papers), Topic Modeling (49 papers) and Speech and dialogue systems (16 papers). Michael Elhadad is often cited by papers focused on Natural Language Processing Techniques (58 papers), Topic Modeling (49 papers) and Speech and dialogue systems (16 papers). Michael Elhadad collaborates with scholars based in Israel, United States and Czechia. Michael Elhadad's co-authors include Regina Barzilay, Yoav Goldberg, Kathleen McKeown, Raphael Cohen, Jacques Robin, Meni Adler, Noémie Elhadad, Hongyan Jing, Tal Baumel and Shay Zakov and has published in prestigious journals such as PLoS ONE, BMC Bioinformatics and Journal of the American Medical Informatics Association.

In The Last Decade

Michael Elhadad

72 papers receiving 1.9k citations

Hit Papers

Using lexical chains for text summarization 1997 2026 2006 2016 1997 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Elhadad Israel 21 1.9k 249 245 172 66 73 2.3k
Aitor Soroa Spain 22 2.0k 1.1× 261 1.0× 290 1.2× 150 0.9× 48 0.7× 77 2.2k
Suresh Manandhar United Kingdom 22 4.1k 2.1× 544 2.2× 275 1.1× 147 0.9× 50 0.8× 90 4.2k
Ivan Vulić United Kingdom 30 2.5k 1.3× 241 1.0× 136 0.6× 513 3.0× 58 0.9× 157 2.8k
Ahmed Rafea Egypt 20 1.5k 0.8× 389 1.6× 113 0.5× 111 0.6× 27 0.4× 88 1.8k
Yue Wang China 22 1.1k 0.6× 336 1.3× 596 2.4× 186 1.1× 107 1.6× 156 1.8k
Dani Yogatama United States 17 1.5k 0.8× 211 0.8× 95 0.4× 205 1.2× 56 0.8× 30 1.8k
Bill MacCartney United States 13 2.0k 1.1× 345 1.4× 302 1.2× 204 1.2× 47 0.7× 15 2.3k
Paul Buitelaar Ireland 19 1.6k 0.8× 400 1.6× 372 1.5× 95 0.6× 63 1.0× 163 1.8k
Zuhair Bandar United Kingdom 16 1.4k 0.8× 436 1.8× 179 0.7× 106 0.6× 78 1.2× 59 1.8k
Leah S. Larkey United States 16 1.1k 0.6× 476 1.9× 142 0.6× 129 0.8× 66 1.0× 22 1.4k

Countries citing papers authored by Michael Elhadad

Since Specialization
Citations

This map shows the geographic impact of Michael Elhadad's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Elhadad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Elhadad more than expected).

Fields of papers citing papers by Michael Elhadad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Elhadad. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Elhadad. The network helps show where Michael Elhadad may publish in the future.

Co-authorship network of co-authors of Michael Elhadad

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Elhadad. A scholar is included among the top collaborators of Michael Elhadad based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Elhadad. Michael Elhadad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Eyal, Matan, Tal Baumel, & Michael Elhadad. (2019). Question Answering as an Automatic Evaluation Metric for News Article Summarization. 3938–3948. 50 indexed citations
2.
Elhadad, Michael, et al.. (2016). The Hebrew FrameNet Project.. Language Resources and Evaluation. 4341–4347. 6 indexed citations
3.
Cohen, Raphael & Michael Elhadad. (2013). Effect of Out Of Vocabulary Terms on Inferring Eligibility Criteria for a Retrospective Study in Hebrew EHR. Meeting of the Association for Computational Linguistics. 116–119. 1 indexed citations
4.
Cohen, Raphael, Michael Elhadad, & Ohad S. Birk. (2013). Analysis of Free Online Physician Advice Services. PLoS ONE. 8(3). e59963–e59963. 6 indexed citations
5.
Elhadad, Michael, Sabino Miranda‐Jiménez, Josef Steinberger, & George Giannakopoulos. (2013). Multi-document multilingual summarization corpus preparation, Part 2: Czech, Hebrew and Spanish. 13–19. 8 indexed citations
6.
Cohen, Raphael, Yoav Goldberg, & Michael Elhadad. (2012). Domain Adaptation of a Dependency Parser with a Class-Class Selectional Preference Model. Meeting of the Association for Computational Linguistics. 43–48. 5 indexed citations
7.
Goldberg, Yoav & Michael Elhadad. (2011). Joint Hebrew Segmentation and Parsing using a PCFGLA Lattice Parser. Meeting of the Association for Computational Linguistics. 704–709. 18 indexed citations
8.
Zakov, Shay, Yoav Goldberg, Michael Elhadad, & Michal Ziv-Ukelson. (2011). Rich Parameterization Improves RNA Structure Prediction. Journal of Computational Biology. 18(11). 1525–1542. 68 indexed citations
9.
Cohen, Raphael, et al.. (2011). CSI-OMIM - Clinical Synopsis Search in OMIM. BMC Bioinformatics. 12(1). 65–65. 13 indexed citations
10.
Goldberg, Yoav & Michael Elhadad. (2010). Inspecting the Structural Biases of Dependency Parsing Algorithms. 234–242. 8 indexed citations
11.
Goldberg, Yoav & Michael Elhadad. (2010). An Efficient Algorithm for Easy-First Non-Directional Dependency Parsing. North American Chapter of the Association for Computational Linguistics. 742–750. 134 indexed citations
12.
Goldberg, Yoav & Michael Elhadad. (2010). Easy-First Dependency Parsing of Modern Hebrew. North American Chapter of the Association for Computational Linguistics. 103–107. 17 indexed citations
13.
Goldberg, Yoav, Meni Adler, & Michael Elhadad. (2008). EM Can Find Pretty Good HMM POS-Taggers (When Given a Good Start). Meeting of the Association for Computational Linguistics. 746–754. 44 indexed citations
14.
Adler, Meni, et al.. (2008). Unsupervised Lexicon-Based Resolution of Unknown Words for Full Morphological Analysis. Meeting of the Association for Computational Linguistics. 728–736. 18 indexed citations
15.
Goldberg, Yoav & Michael Elhadad. (2007). SVM Model Tampering and Anchored Learning: A Case Study in Hebrew NP Chunking. Meeting of the Association for Computational Linguistics. 224–231. 7 indexed citations
16.
Elhadad, Michael, Mira Balaban, & Arnon Sturm. (2007). Effective Business Process Outsourcing: The Prosero Approach. Ibis. 6(3). 8–31. 9 indexed citations
17.
Elhadad, Michael, et al.. (1998). Generation Of Noun Compounds In Hebrew: Can Syntactic Knowledge Be Fully Encapsulated?. 4 indexed citations
18.
Elhadad, Michael, et al.. (1998). SURGE: a Comprehensive Plug-in Syntactic Realization Component for Text Generation. 2 indexed citations
19.
Elhadad, Michael, Steven Feiner, Kathleen McKeown, & Dorée Duncan Seligmann. (1991). Generating customized text and graphics in the COMET explanation testbed. Winter Simulation Conference. 1058–1065. 2 indexed citations
20.
McKeown, Kathleen, et al.. (1990). Natural language generation in COMET. 103–139. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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