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.
Countries citing papers authored by Gabriel Murray
Since
Specialization
Citations
This map shows the geographic impact of Gabriel Murray'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 Gabriel Murray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Murray more than expected).
This network shows the impact of papers produced by Gabriel Murray. 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 Gabriel Murray. The network helps show where Gabriel Murray may publish in the future.
Co-authorship network of co-authors of Gabriel Murray
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Murray.
A scholar is included among the top collaborators of Gabriel Murray 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 Gabriel Murray. Gabriel Murray is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Murray, Gabriel, Giuseppe Carenini, & Shafiq Joty. (2018). NLP for Conversations: Sentiment, Summarization, and Group Dynamics. International Conference on Computational Linguistics. 1–4.1 indexed citations
Murray, Gabriel, Giuseppe Carenini, & Raymond T. Ng. (2012). Using the Omega Index for Evaluating Abstractive Community Detection. North American Chapter of the Association for Computational Linguistics. 10–18.12 indexed citations
9.
Murray, Gabriel, Giuseppe Carenini, & Raymond T. Ng. (2010). Interpretation and Transformation for Abstracting Conversations. North American Chapter of the Association for Computational Linguistics. 894–902.17 indexed citations
10.
Murray, Gabriel, Giuseppe Carenini, & Raymond T. Ng. (2010). Generating and validating abstracts of meeting conversations: a user study. 105–113.38 indexed citations
Murray, Gabriel, Shafiq Joty, Giuseppe Carenini, & Raymond T. Ng. (2008). The University of British Columbia at TAC 2008. Theory and applications of categories.3 indexed citations
13.
Murray, Gabriel & Steve Renals. (2007). 8th Annual Conference of the International Speech Communication Association. Conference of the International Speech Communication Association.123 indexed citations
14.
Murray, Gabriel, Steve Renals, Jean Carletta, & Johanna D. Moore. (2006). Proceedings of the Human Language Technology Conference of the NAACL, Main Conference.29 indexed citations
Murray, Gabriel, Steve Renals, Jean Carletta, & Johanna D. Moore. (2005). Evaluating Automatic Summaries of Meeting Recordings. ERA. 33–40.48 indexed citations
Murray, Gabriel, Steve Renals, & Jean Carletta. (2005). 9th European Conference on Speech Communication and Technology (Interspeech 2005 - Eurospeech). Conference of the International Speech Communication Association.2 indexed citations
20.
Murray, Gabriel, et al.. (2002). WQ: An Environment for Teaching Information Access Skills. EdMedia: World Conference on Educational Media and Technology. 2002(1). 34–39.4 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.