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.
Mining the peanut gallery
20031.3k citationsSteve Lawrence, David M. Pennock et al.profile →
Accessibility of information on the web
1999881 citationsSteve Lawrence, C. Lee Gilesprofile →
Searching the World Wide Web
1998645 citationsSteve Lawrence, C. Lee GilesScienceprofile →
CiteSeer
1998620 citationsC. Lee Giles, Kurt Bollacker et al.profile →
Countries citing papers authored by Steve Lawrence
Since
Specialization
Citations
This map shows the geographic impact of Steve Lawrence'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 Steve Lawrence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Lawrence more than expected).
This network shows the impact of papers produced by Steve Lawrence. 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 Steve Lawrence. The network helps show where Steve Lawrence may publish in the future.
Co-authorship network of co-authors of Steve Lawrence
This figure shows the co-authorship network connecting the top 25 collaborators of Steve Lawrence.
A scholar is included among the top collaborators of Steve Lawrence 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 Steve Lawrence. Steve Lawrence 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.
Lawrence, Steve, et al.. (2012). ENHANCING SEAMLESS DATA TRANSFER WITHIN COMPLEX MESH ENVIRONMENTS WITH SECURE AGENTS. 187–198.
Whitman, Brian & Steve Lawrence. (2002). Inferring Descriptions and Similarity for Music from Community Metadata. The Journal of the Abraham Lincoln Association. 2002.79 indexed citations
Lawrence, Steve. (2000). Context in Web Search.. IEEE Data(base) Engineering Bulletin. 23. 25–32.145 indexed citations
11.
Diligenti, Michelangelo, Frans Coetzee, Steve Lawrence, C. Lee Giles, & Marco Gori. (2000). Focused Crawling Using Context Graphs. Very Large Data Bases. 527–534.330 indexed citations
12.
Lawrence, Steve & C. Lee Giles. (1999). Text and Image Metasearch on the Web.. Parallel and Distributed Processing Techniques and Applications. 829–835.5 indexed citations
13.
Lawrence, Steve & C. Lee Giles. (1998). Inquirus, the NECI meta search engine.2 indexed citations
Giles, C. Lee, Kurt Bollacker, & Steve Lawrence. (1998). CiteSeer. 89–98.620 indexed citations breakdown →
16.
Lawrence, Steve, C. Lee Giles, & Sandiway Fong. (1998). On the Applicability of Neural Network and Machine Learning Methodologies to Natural Language Processing. Digital Repository at the University of Maryland (University of Maryland College Park).5 indexed citations
17.
Giles, C. Lee & Steve Lawrence. (1997). Presenting and analyzing the results of ai experiments: data averaging and data snooping. National Conference on Artificial Intelligence. 362–367.3 indexed citations
18.
Lawrence, Steve, C. Lee Giles, & Ah Chung Tsoi. (1997). Lessons in neural network training: overfitting may be harder than expected. National Conference on Artificial Intelligence. 540–545.170 indexed citations
19.
Lawrence, Steve, et al.. (1996). A Site Survey of Masonry Bond Strength. 38. 103–109.9 indexed citations
20.
Lawrence, Steve, Ah Chung Tsoi, & Andrew D. Back. (1995). The Gamma MLP for Speech Phoneme Recognition. Neural Information Processing Systems. 8. 785–791.9 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.