Amal Shehan Perera

493 citations
62 papers · 280 indexed · h-index 9
Topics
Data Mining Algorithms and Applications (10 papers)Topic Modeling (9 papers)Artificial Intelligence in Law (8 papers)
Journals
SHILAP Revista de lepidopterologíaIEEE AccessInternational Journal of Remote Sensing

In The Last Decade

Amal Shehan Perera

57 papers receiving 260 citations

Peers

Amal Shehan Perera
Comparison fields: 5 of 68
  • Artificial Intelligence 109
  • Signal Processing 51
  • Computer Vision and Pattern Recognition 45
  • Information Systems 42
  • Ocean Engineering 36
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Citations per field
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Citations per year

Countries citing papers authored by Amal Shehan Perera

Since Specialization
Citations

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

Fields of papers citing papers by Amal Shehan Perera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amal Shehan Perera. 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 Amal Shehan Perera. The network helps show where Amal Shehan Perera may publish in the future.

Co-authorship network of co-authors of Amal Shehan Perera

This figure shows the co-authorship network connecting the top 25 collaborators of Amal Shehan Perera. A scholar is included among the top collaborators of Amal Shehan Perera 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 Amal Shehan Perera. Amal Shehan Perera 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
#WorkIndexed citations
1 6
2 1
3 1
4 2
5 2
6 1
7 4
8 6
9 6
10 34
11
Experimental Study on Item-based P-Tree Collaborative Filtering Algorithm for Netflix.
2
12
Gene Function Prediction.
4
13
A Comparative Study on Data Representation to Categorize Text Documents.
5
14
Parameter Optimized, Vertical, Nearest-Neighbor-Vote and Boundary-Based Classification.
1
15
Vertical K-Median Clustering.
0
16
Vertical Set Square Distance Based Clustering without Prior Knowledge of K.
3
17
An Api for Transparent Distributed Vertical Data Mining.
1
18
Multi-Layered Framework for Distributed Data Mining.
3
19
Genetic Algorithm to Improve a Solution for a General Assignment Problem.
3
20
Performance Improvement for Bayesian Classification on Spatial Data with P-Trees.
1

About Amal Shehan Perera

Amal Shehan Perera is a scholar working on Artificial Intelligence, Signal Processing and Computer Science Applications, having authored 62 papers that have together received 280 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (10 papers), Topic Modeling (9 papers) and Artificial Intelligence in Law (8 papers). The work is most often cited by research in Signal Processing (51 citations), Artificial Intelligence (109 citations) and Ocean Engineering (36 citations). Amal Shehan Perera has collaborated with scholars based in Sri Lanka, United States and Australia. Frequent co-authors include Nisansa de Silva, Dulani Meedeniya, William Perrizo, Damminda Alahakoon, Anne Denton, Rashmika Nawaratne, Chandi Witharana, Daswin De Silva, Anna Liljedahl and Gayashan Amarasinghe. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and International Journal of Remote Sensing.

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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