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.
This map shows the geographic impact of Owen Rambow'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 Owen Rambow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Owen Rambow more than expected).
This network shows the impact of papers produced by Owen Rambow. 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 Owen Rambow. The network helps show where Owen Rambow may publish in the future.
Co-authorship network of co-authors of Owen Rambow
This figure shows the co-authorship network connecting the top 25 collaborators of Owen Rambow.
A scholar is included among the top collaborators of Owen Rambow 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 Owen Rambow. Owen Rambow is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rambow, Owen, et al.. (2020). Email Classification Incorporating Social Networks and Thread Structure.. Language Resources and Evaluation. 1336–1345.3 indexed citations
4.
Bouamor, Houda, Nizar Habash, Mohammad Salameh, et al.. (2018). The madar Arabic dialect corpus and lexicon. Language Resources and Evaluation. 3387–3396.106 indexed citations
5.
Hirschberg, Julia, et al.. (2016). Incrementally Learning a Dependency Parser to Support Language Documentation in Field Linguistics. International Conference on Computational Linguistics. 440–449.1 indexed citations
Habash, Nizar, et al.. (2013). DIRA: Dialectal Arabic Information Retrieval Assistant. International Joint Conference on Natural Language Processing. 13–16.6 indexed citations
9.
Agarwal, Apoorv, et al.. (2012). Social Network Analysis of Alice in Wonderland. North American Chapter of the Association for Computational Linguistics. 88–96.47 indexed citations
10.
Prabhakaran, Vinodkumar, et al.. (2012). Annotations for Power Relations on Email Threads. Language Resources and Evaluation. 806–811.8 indexed citations
Habash, Nizar, et al.. (2011). Fast Yet Rich Morphological Analysis. 116–124.10 indexed citations
13.
Agarwal, Apoorv, Owen Rambow, & Rebecca J. Passonneau. (2010). Annotation Scheme for Social Network Extraction from Text. 20–28.13 indexed citations
14.
Freitag, Dayne, et al.. (2008). Improving NER in Arabic Using a Morphological Tagger.. Language Resources and Evaluation. 2509–2514.26 indexed citations
15.
Rambow, Owen, Bonnie J. Dorr, David Farwell, et al.. (2006). Parallel syntactic annotation of multiple languages. Language Resources and Evaluation. 559–564.9 indexed citations
16.
Rambow, Owen, et al.. (2002). A Dependency Treebank for English. Language Resources and Evaluation.22 indexed citations
17.
Bangalore, Srinivas, John Chen, & Owen Rambow. (2001). Impact of Quality and Quantity of Corpora on Stochastic Generation. Empirical Methods in Natural Language Processing.7 indexed citations
18.
Rambow, Owen & Beatrice Santorini. (1995). Incremental Phrase Structure Generation and a Universal Theory of V2. Scholarworks (University of Massachusetts Amherst). 25(1). 26.3 indexed citations
19.
Vijay‐Shanker, K., David Weir, & Owen Rambow. (1995). Parsing D-Tree Grammars. Sussex Research Online (University of Sussex). 252–259.9 indexed citations
20.
Rambow, Owen. (1990). Domain Communication Knowledge.14 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.