M. Lilly Florence

505 total citations
17 papers, 342 citations indexed

About

M. Lilly Florence is a scholar working on Information Systems, Software and Computer Networks and Communications. According to data from OpenAlex, M. Lilly Florence has authored 17 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Information Systems, 7 papers in Software and 6 papers in Computer Networks and Communications. Recurrent topics in M. Lilly Florence's work include Software Engineering Research (8 papers), Software Reliability and Analysis Research (6 papers) and Software System Performance and Reliability (4 papers). M. Lilly Florence is often cited by papers focused on Software Engineering Research (8 papers), Software Reliability and Analysis Research (6 papers) and Software System Performance and Reliability (4 papers). M. Lilly Florence collaborates with scholars based in India, United States and Japan. M. Lilly Florence's co-authors include Arti Arya and has published in prestigious journals such as Journal of Medical Systems, Cluster Computing and International Journal of Computer Applications in Technology.

In The Last Decade

M. Lilly Florence

16 papers receiving 319 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M. Lilly Florence India	8	286	250	141	67	33	17	342
An Ngoc Lam Norway	7	271 0.9×	164 0.7×	120 0.9×	68 1.0×	84 2.5×	11	325
Huayao Wu China	8	128 0.4×	203 0.8×	53 0.4×	57 0.9×	25 0.8×	30	293
Rajni Mohana India	7	168 0.6×	56 0.2×	97 0.7×	78 1.2×	40 1.2×	23	255
Vandana Bhattacherjee India	9	184 0.6×	138 0.6×	86 0.6×	86 1.3×	19 0.6×	31	262
Breno Miranda Brazil	11	330 1.2×	388 1.6×	126 0.9×	53 0.8×	38 1.2×	42	473
Chengsong Wang China	6	320 1.1×	378 1.5×	74 0.5×	38 0.6×	45 1.4×	15	439
Xiaolin Ju China	9	202 0.7×	180 0.7×	78 0.6×	53 0.8×	50 1.5×	38	278
Tian Jiang China	6	263 0.9×	195 0.8×	184 1.3×	65 1.0×	67 2.0×	9	373
Brady J. Garvin United States	6	238 0.8×	301 1.2×	91 0.6×	158 2.4×	19 0.6×	6	380
Kalpesh Kapoor India	8	126 0.4×	289 1.2×	78 0.6×	65 1.0×	28 0.8×	25	365

Countries citing papers authored by M. Lilly Florence

Since Specialization

Citations

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

Fields of papers citing papers by M. Lilly Florence

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Lilly Florence. 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 M. Lilly Florence. The network helps show where M. Lilly Florence may publish in the future.

Co-authorship network of co-authors of M. Lilly Florence

This figure shows the co-authorship network connecting the top 25 collaborators of M. Lilly Florence. A scholar is included among the top collaborators of M. Lilly Florence 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 M. Lilly Florence. M. Lilly Florence is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

17 of 17 papers shown

Florence, M. Lilly, et al.. (2022). Machine Learning Based Predictive Analysis of Diseases in Health Care. 2021. 1–7. 3 indexed citations

Florence, M. Lilly, et al.. (2022). Agriculture Crop Selection and Yield Prediction using Machine Learning Algorithms. 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS). 510–517. 9 indexed citations

Florence, M. Lilly, et al.. (2022). Estimation and Prediction of Crop Yielding Rate Using Machine Learning Techniques. 2022 International Conference on Computer Communication and Informatics (ICCCI). 1–5. 4 indexed citations

Florence, M. Lilly, et al.. (2021). Evaluating the Performance of Various Deep Reinforcement Learning Algorithms for a Conversational Chatbot. 2021 2nd International Conference for Emerging Technology (INCET). 1–8. 6 indexed citations

Florence, M. Lilly, et al.. (2019). Securing Personal Health Record System in Cloud Using User Usage Based Encryption. Journal of Medical Systems. 43(6). 171–171. 9 indexed citations

Florence, M. Lilly, et al.. (2019). Improved Bayesian regularisation using neural networks based on feature selection for software defect prediction. International Journal of Computer Applications in Technology. 60(3). 225–225. 1 indexed citations

Florence, M. Lilly, et al.. (2018). Deep neural network based hybrid approach for software defect prediction using software metrics. Cluster Computing. 22(S4). 9847–9863. 141 indexed citations

Florence, M. Lilly, et al.. (2018). Software defect prediction techniques using metrics based on neural network classifier. Cluster Computing. 22(S1). 77–88. 90 indexed citations

Florence, M. Lilly, et al.. (2018). Optimized Machine Learning Approach for Software Defect Prediction using K-means with Genetic Algorithms. International Journal of Computer Sciences and Engineering. 6(9). 385–390. 1 indexed citations

10.

Florence, M. Lilly, et al.. (2018). Hybrid Approach For Software Defect Prediction Using Machine Learning With Optimization Technique. Zenodo (CERN European Organization for Nuclear Research). 9 indexed citations

11.

Florence, M. Lilly, et al.. (2017). Enhanced secure sharing of PHR’s in cloud using user usage based attribute based encryption and signature with keyword search. Cluster Computing. 22(S6). 13119–13130. 10 indexed citations

12.

Florence, M. Lilly, et al.. (2017). A Review on Software Defect Prediction Techniques Using Product Metrics. International Journal of Database Theory and Application. 10(1). 163–174. 5 indexed citations

13.

Florence, M. Lilly, et al.. (2016). A Theoretical Approach towards Data Preprocessing Techniques in Data Mining – A Survey. International Journal of u- and e- Service Science and Technology. 9(11). 421–428.

14.

Florence, M. Lilly, et al.. (2015). A Study on Software Metrics based Software Defect Prediction using Data Mining and Machine Learning Techniques. International Journal of Database Theory and Application. 8(3). 179–190. 41 indexed citations

15.

Florence, M. Lilly, et al.. (2012). An Overview of Software Reliability Models. 11 indexed citations

16.

Florence, M. Lilly, et al.. (2011). A SURVEY ON WIRELESS SENSOR NETWORK ARCHITECTURE, PROTOCOLS AND APPLICATIONS. Journal of Global Research in Computer Sciences. 2(7). 149–152. 1 indexed citations

17.

Florence, M. Lilly, et al.. (2011). SECURITY ISSUES IN COMPUTER NETWORK ARCHITECTURE. Journal of Global Research in Computer Sciences. 2(7). 153–156. 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.

Explore authors with similar magnitude of impact