David Carmel

5.6k citations
101 papers · 3.1k · h-index 29

Impact in

    • Information Retrieval and Search Behavior
    • Web Data Mining and Analysis
    • Recommender Systems and Techniques
    • Data Management and Algorithms

Papers in

David Carmel

96 papers receiving 2.8k citations

Peers

David Carmel
Comparison fields: 5 of 92
  • Information Systems 2.0k
  • Signal Processing 618
  • Artificial Intelligence 1.8k
  • Computer Networks and Communications 656
  • Computer Science Applications 153
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Citations per field
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Citations per year

Countries citing papers authored by David Carmel

Since Specialization
Citations

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

Fields of papers citing papers by David Carmel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Carmel, 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 David Carmel Line = papers co-authored together David Carmel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 101 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003280
2 2010194
3
Blocking blog spam with language model disagreement
2005160
4 2009151
5 2006137
6 2009135
7 2001130
8 2010113
9 2003109
10 201294
11
Learning models of intelligent agents
199669
12 201160
13 201360
14 201659
15 200658
16 201457
17 200549
18 201048
19 200247
20
Incorporating opponent models into adversary search
199644

About David Carmel

David Carmel is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Management Science and Operations Research, having authored 101 papers that have together received 3.1k indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (35 papers), Web Data Mining and Analysis (29 papers), Topic Modeling (29 papers), Data Management and Algorithms (19 papers), Advanced Database Systems and Queries (15 papers), Semantic Web and Ontologies (12 papers), Recommender Systems and Techniques (12 papers) and Data Quality and Management (9 papers). The work is most often cited by research in Information Systems (2.0k citations), Signal Processing (618 citations), Artificial Intelligence (1.8k citations), Computer Networks and Communications (656 citations) and Computer Science Applications (153 citations). David Carmel has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Aya Soffer, Elad Yom‐Tov, Ido Guy, Oren Kurland, Shaul Markovitch, Yoelle Maarek, Inbal Ronen, Michael Herscovici, Naama Zwerdling and Andrei Broder. Their work appears in journals such as ACM SIGIR Forum, ACM Transactions on Information Systems, Journal of Architectural Engineering, IBM Journal of Research and Development and Autonomous Agents and Multi-Agent Systems.

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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