This map shows the geographic impact of Rakesh Verma'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 Rakesh Verma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rakesh Verma more than expected).
This network shows the impact of papers produced by Rakesh Verma. 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 Rakesh Verma. The network helps show where Rakesh Verma may publish in the future.
Co-authorship network of co-authors of Rakesh Verma
This figure shows the co-authorship network connecting the top 25 collaborators of Rakesh Verma.
A scholar is included among the top collaborators of Rakesh Verma 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 Rakesh Verma. Rakesh Verma is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Das, Avisha, et al.. (2018). University of Houston @ CL-SciSumm 2018.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 142–149.3 indexed citations
7.
Das, Avisha, et al.. (2017). University of Houston @ CL-SciSumm 2017: Positional language Models, Structural Correspondence Learning and Textual Entailment.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 73–85.4 indexed citations
Verma, Rakesh, et al.. (2015). A New Approach for Idiom Identification Using Meanings and the Web. Recent Advances in Natural Language Processing. 681–687.10 indexed citations
Verma, Rakesh & Ping Chen. (2012). A data mining hypertextbook: design, implementation and experience. Journal of computing sciences in colleges. 27(3). 22–28.2 indexed citations
12.
Chen, Ping, et al.. (2011). Designing an undergraduate data mining course by matching teaching strategies with student learning styles. Journal of computing sciences in colleges. 26(4). 49–56.2 indexed citations
13.
Verma, Rakesh, et al.. (2011). SemQuest: University of Houston's Semantics-based Question Answering System.. Theory and applications of categories.4 indexed citations
14.
Chen, Ping, et al.. (2010). Improving an undergraduate data mining course with real-world projects. Journal of computing sciences in colleges. 25(4). 62–67.1 indexed citations
15.
Verma, Rakesh, et al.. (2010). A Ranking-based Approach for Multiple-document Information Extraction.. Theory and applications of categories.2 indexed citations
16.
Chen, Ping, Rakesh Verma, Janet C. Meininger, & Wenyaw Chan. (2008). Semantic Analysis of Association Rules. The Florida AI Research Society. 270–275.6 indexed citations
Verma, Rakesh. (1995). Unique normal forms and confluence of rewrite systems: persistence. International Joint Conference on Artificial Intelligence. 362–368.1 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.