Nadav Eiron

1.6k citations
17 papers · 883 · h-index 11

Impact in

    • Web Data Mining and Analysis
    • Service-Oriented Architecture and Web Services
    • Information Retrieval and Search Behavior
    • Spam and Phishing Detection
    • Semantic Web and Ontologies
    • Topic Modeling
    • Natural Language Processing Techniques

Papers in

    • Machine Learning and Algorithms 5
    • Semantic Web and Ontologies 4
    • Algorithms and Data Compression 4
    • Advanced Text Analysis Techniques 2
    • Natural Language Processing Techniques 2
    • Web Data Mining and Analysis 10

Nadav Eiron

17 papers receiving 760 citations

Peers

Nadav Eiron
Comparison fields: 5 of 70
  • Information Systems 587
  • Artificial Intelligence 550
  • Signal Processing 97
  • Management Science and Operations Research 106
  • Statistical and Nonlinear Physics 105
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Citations per field
00.5×
Stephen Dill · 1×
Citations per year

Countries citing papers authored by Nadav Eiron

Since Specialization
Citations

This map shows the geographic impact of Nadav Eiron'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 Nadav Eiron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nadav Eiron more than expected).

Fields of papers citing papers by Nadav Eiron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nadav Eiron. 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 Nadav Eiron. The network helps show where Nadav Eiron may publish in the future.

Co-authors

The 22 scholars most cited alongside Nadav Eiron, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nadav Eiron Line = papers co-authored together Nadav Eiron links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2003282
2 2004141
3 2003111
4 200375
5 200656
6 200355
7 199541
8 200239
9 200330
10 200318
11
Locality, Hierarchy, and Bidirectionality in the Web∗
200313
12 20038
13 19988
14 20022
15 20052
16 20031
17 20031

About Nadav Eiron

Nadav Eiron is a scholar working on Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics, Computer Networks and Communications and Management Science and Operations Research, having authored 17 papers that have together received 883 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (10 papers), Machine Learning and Algorithms (5 papers), Complex Network Analysis Techniques (4 papers), Semantic Web and Ontologies (4 papers), Algorithms and Data Compression (4 papers), Optimization and Search Problems (2 papers), Advanced Text Analysis Techniques (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Information Systems (587 citations), Artificial Intelligence (550 citations), Signal Processing (97 citations), Management Science and Operations Research (106 citations) and Statistical and Nonlinear Physics (105 citations). Nadav Eiron has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Kevin S. McCurley, John A. Tomlin, Anant Jhingran, Daniel Gruhl, Sridhar Rajagopalan, Andrew Tomkins, Jason Y. Zien, Stephen Dill, David Gibson and Tapas Kanungo. Their work appears in journals such as Journal of Computer and System Sciences, Theoretical Computer Science, Machine Learning, Journal of Web Semantics and SSRN Electronic Journal.

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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