Ray R. Hashemi

515 total citations
66 papers, 324 citations indexed

About

Ray R. Hashemi is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Ray R. Hashemi has authored 66 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 17 papers in Information Systems and 17 papers in Computational Theory and Mathematics. Recurrent topics in Ray R. Hashemi's work include Rough Sets and Fuzzy Logic (15 papers), Data Mining Algorithms and Applications (10 papers) and Data Management and Algorithms (7 papers). Ray R. Hashemi is often cited by papers focused on Rough Sets and Fuzzy Logic (15 papers), Data Mining Algorithms and Applications (10 papers) and Data Management and Algorithms (7 papers). Ray R. Hashemi collaborates with scholars based in United States, Ireland and Iran. Ray R. Hashemi's co-authors include M. H. Kargarnovin, John R. Talburt, John F. Young, F. Choobineh, Frederick R. Jelovsek, Mehdi Razzaghi, Fernando Gustavo Tinetti, Hamid R. Arabnia, Lei Jin and Gary Anderson and has published in prestigious journals such as European Journal of Operational Research, Annals of the New York Academy of Sciences and Expert Systems with Applications.

In The Last Decade

Ray R. Hashemi

56 papers receiving 288 citations

Peers

Ray R. Hashemi
Comparison fields: 5 of 87
  • Artificial Intelligence 100
  • Computational Theory and Mathematics 74
  • Information Systems 69
  • Management Science and Operations Research 48
  • Ocean Engineering 34
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Citations per field, relative to Ray R. Hashemi
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Citations per year, relative to Ray R. Hashemi
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Countries citing papers authored by Ray R. Hashemi

Since Specialization
Citations

This map shows the geographic impact of Ray R. Hashemi'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 Ray R. Hashemi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ray R. Hashemi more than expected).

Fields of papers citing papers by Ray R. Hashemi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ray R. Hashemi. 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 Ray R. Hashemi. The network helps show where Ray R. Hashemi may publish in the future.

Co-authorship network of co-authors of Ray R. Hashemi

This figure shows the co-authorship network connecting the top 25 collaborators of Ray R. Hashemi. A scholar is included among the top collaborators of Ray R. Hashemi 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 Ray R. Hashemi. Ray R. Hashemi 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
# Work Indexed citations
1 4
2 0
3 0
4
Information and Knowledge Engineering
1
5
A Concept-based Feature Extraction Approach
1
6
Identification of Human Skin Regions Using Color and Texture
1
7
Association Analysis of the Working Environment and SOD Enzyme Behavior of Workers in a Factory Setting
0
8
A Formal Framework for Defining Entity-Based Data Source Integration
4
9
Discovery of Intent through the Analysis of Visited Sites
2
10
Entity Identification Using Indexed Entity Catalogs.
3
11 1
12 2
13
Spam Detection: A Syntax and Semantic-Based Approach
2
14
LEFRA: learning from associations
1
15 13
16 1
17 8
18
Extraction of Features with Unstructured Representation from HTML Documents.
6
19 3
20
VESSEL ACCIDENT MODELING: A COMPARISON OF NEURAL NETWORKS, DISCRIMINANT ANALYSIS AND LOGISTIC REGRESSION
1

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.

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