Ed H.

21.6k citations
174 papers · 9.8k indexed · 6 hit papers · h-index 49

Ed H.

164 papers receiving 9.1k citations

Hit Papers

Challenging ...12120082026201420204008001.2k

Peers

Ed H.
Comparison fields: 5 of 172
  • Computer Science Applications 1.9k
  • Communication 1.7k
  • Information Systems 3.8k
  • Human-Computer Interaction 836
  • Artificial Intelligence 3.3k
Replace Loren Terveen with:
Loren Terveen United States
Peter Pirolli United States
Dan Cosley United States
Jaime Teevan United States
Mark S. Ackerman United States
Bernard J. Jansen United States
Aniket Kittur United States
Bongwon Suh South Korea
Éric Gilbert United States
Mor Naaman United States
Ed H. relative to Loren Terveen United States Loren Terveen's profile →
Citations per field
00.5×10×
Loren Terveen · 1×
Citations per year

Countries citing papers authored by Ed H.

Since Specialization
Citations

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

Fields of papers citing papers by Ed H.

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20240
3 20241
4 20240
5 20246
6
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Thembreakdown →
2023121
7 20239
8 20232
9 20234
10 20236
11 20235
12 20231
13 20234
14
Batch Reinforcement Learning Through Continuation Method
20213
15
DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems.
20205
16
SageDB: A Learned Database System
201970
17
Proceedings of the SIGCHI Conference on Human Factors in Computing Systemsbreakdown →
2012354
18
Augmented Social Cognition.
200811
19 2002285
20
LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition
20020

About Ed H.

Ed H. is a scholar working on Computer Science Applications, Human-Computer Interaction and Information Systems, having authored 174 papers that have together received 9.8k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (48 papers), Mobile Crowdsensing and Crowdsourcing (26 papers), Advanced Bandit Algorithms Research (24 papers), Topic Modeling (22 papers), Wikis in Education and Collaboration (17 papers), Data Visualization and Analytics (16 papers), Information Retrieval and Search Behavior (16 papers) and Advanced Text Analysis Techniques (15 papers). The work is most often cited by research in Computer Science Applications (1.9k citations), Communication (1.7k citations) and Information Systems (3.8k citations). Ed H. has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Bongwon Suh, Aniket Kittur, Lichan Hong, Peter Pirolli, Jilin Chen, Xinyang Yi, Zhe Zhao, Joseph A. Konstan, James E. Pitkow and Bryan A. Pendleton. Their work appears in journals such as Communications of the ACM, Computer, IEEE Internet Computing, IEEE Pervasive Computing and ACM Transactions on Interactive Intelligent 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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