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Researcher · Saveetha University · India

N. Legapriyadharshini

N. Legapriyadharshini publishes mostly in Artificial Intelligence, Management Science and Operations Research and Accounting, on topics such as Imbalanced Data Classification Techniques, Financial Distress and Bankruptcy Prediction and Stock Market Forecasting Methods.

OpenAlex
World rank
#687,485
of 1,633,909 ranked researchers
Rank in India
#9,809
of 44,512
Works
16
Citations
10
Citations per work
0.6

What does N. Legapriyadharshini research?

Artificial Intelligence: 33.3%Management Science and Operations Research: 33.3%Accounting: 33.3%33%top field
Artificial Intelligence33.3%Management Science and Operations Research33.3%Accounting33.3%

Shares of their own output, by the field each of their topics belongs to. The grey slice is everything not listed.

  1. 1Artificial Intelligence33% of their works
  2. 2Management Science and Operations Research33% of their works
  3. 3Accounting33% of their works

Research topics

Which keywords describe N. Legapriyadharshini's research?

The keywords of their largest research topics: Neural Networks, Support Vector Machines, Bankruptcy Prediction, Classification, Credit Scoring, Imbalanced Data, Stock Market Prediction and Time Series Forecasting.

Size is their works in the topics tagged with each word, from their 3 largest topics. Each links to the topic it comes from most.

All 8 words, with their numbers
  1. Neural Networks22 topics
  2. Support Vector Machines22 topics
  3. Bankruptcy Prediction11 topic
  4. Classification11 topic
  5. Credit Scoring11 topic
  6. Imbalanced Data11 topic
  7. Stock Market Prediction11 topic
  8. Time Series Forecasting11 topic

Where does N. Legapriyadharshini work?

N. Legapriyadharshini's main affiliation in the publication record is Saveetha University, India.

How many publications and citations does N. Legapriyadharshini have?

Science Explorer counts 16 works and 10 citations for N. Legapriyadharshini, ranking #687,485 of 1,633,909 researchers worldwide on the composite score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics are in the interactive view on the map. Is this your page? Request a correction or removal.