Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Guidelines for Human-AI Interaction
2019841 citationsSaleema Amershi, Dan Weld et al.profile →
Countries citing papers authored by Paul N. Bennett
Since
Specialization
Citations
This map shows the geographic impact of Paul N. Bennett'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 Paul N. Bennett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul N. Bennett more than expected).
This network shows the impact of papers produced by Paul N. Bennett. 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 Paul N. Bennett. The network helps show where Paul N. Bennett may publish in the future.
Co-authorship network of co-authors of Paul N. Bennett
This figure shows the co-authorship network connecting the top 25 collaborators of Paul N. Bennett.
A scholar is included among the top collaborators of Paul N. Bennett 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 Paul N. Bennett. Paul N. Bennett is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhao, Chen, Chenyan Xiong, Corby Rosset, et al.. (2020). Transformer-XH: Multi-Evidence Reasoning with eXtra Hop Attention. International Conference on Learning Representations.62 indexed citations
6.
Amershi, Saleema, Dan Weld, Mihaela Vorvoreanu, et al.. (2019). Guidelines for Human-AI Interaction. 1–13.841 indexed citations breakdown →
7.
Bennett, Paul N.. (2015). Search from Personal to Social Context: Progress and Challenges.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 2.
8.
Bennett, Paul N. & Emre Kıcıman. (2015). Persona-ization: Searching on Behalf of Others. International ACM SIGIR Conference on Research and Development in Information Retrieval. 26–32.2 indexed citations
9.
Bennett, Paul N. & Ryen W. White. (2015). Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track. Text REtrieval Conference.1 indexed citations
Collins‐Thompson, Kevyn, Craig Macdonald, Paul N. Bennett, Fernando Díaz, & Ellen M. Voorhees. (2013). TREC 2013 Web Track Overview. Text REtrieval Conference.36 indexed citations
Pfeiffer, Joseph J., Jennifer Neville, & Paul N. Bennett. (2012). Active Sampling of Networks.8 indexed citations
14.
Kotov, Alexander, Paul N. Bennett, Ryen W. White, Susan Dumais, & Jaime Teevan. (2011). Modeling and Analyses of Multi-Session Search Tasks. International ACM SIGIR Conference on Research and Development in Information Retrieval.2 indexed citations
15.
Bennett, Paul N., Raman Chandrasekar, Max Chickering, et al.. (2009). Proceedings of the ACM SIGKDD Workshop on Human Computation. Knowledge Discovery and Data Mining.1 indexed citations
16.
Radlinski, Filip, Paul N. Bennett, & Ben Carterette. (2009). Redundancy, Diversity, and Interdependent Document Relevance, a summary of the SIGIR 2009 workshop. ACM SIGIR Forum.1 indexed citations
Bennett, Paul N. & Jaime Carbonell. (2007). Combining Probability-Based Rankers for Action-Item Detection. North American Chapter of the Association for Computational Linguistics. 324–331.6 indexed citations
19.
Bennett, Paul N. & Jaime Carbonell. (2005). Feature Representation for Effective Action-Item Detection. International ACM SIGIR Conference on Research and Development in Information Retrieval.2 indexed citations
20.
Bennett, Paul N., Susan Dumais, & Eric Horvitz. (2003). Inductive Transfer for Text Classification using Generalized Reliability Indicators. International Conference on Machine Learning.9 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.