Inay Ha

468 total citations
15 papers, 299 citations indexed

About

Inay Ha is a scholar working on Information Systems, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Inay Ha has authored 15 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Information Systems, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in Inay Ha's work include Recommender Systems and Techniques (9 papers), Digital Marketing and Social Media (3 papers) and Augmented Reality Applications (2 papers). Inay Ha is often cited by papers focused on Recommender Systems and Techniques (9 papers), Digital Marketing and Social Media (3 papers) and Augmented Reality Applications (2 papers). Inay Ha collaborates with scholars based in South Korea, United States and Canada. Inay Ha's co-authors include Geun‐Sik Jo, Heung-Nam Kim, Abdulmotaleb El-Saddik, Kyungyong Chung, Ulrich Neumann and Suya You and has published in prestigious journals such as Decision Support Systems, Multimedia Tools and Applications and Electronic Commerce Research and Applications.

In The Last Decade

Inay Ha

12 papers receiving 282 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Inay Ha South Korea 6 231 90 81 54 43 15 299
Miguel A. Rueda-Morales Spain 6 244 1.1× 97 1.1× 89 1.1× 37 0.7× 24 0.6× 7 280
Sheetal Girase India 6 230 1.0× 88 1.0× 119 1.5× 28 0.5× 30 0.7× 14 295
Inma Garcia Spain 6 208 0.9× 41 0.5× 78 1.0× 105 1.9× 31 0.7× 7 306
Sunita Barve India 7 174 0.8× 67 0.7× 128 1.6× 29 0.5× 20 0.5× 36 313
Yan‐Shuo Chang China 6 183 0.8× 98 1.1× 130 1.6× 34 0.6× 14 0.3× 15 283
Deepa Anand India 8 169 0.7× 52 0.6× 180 2.2× 49 0.9× 16 0.4× 21 327
Bogdan Walek Czechia 6 181 0.8× 53 0.6× 118 1.5× 37 0.7× 26 0.6× 33 267
Rahul Pandey United States 4 222 1.0× 79 0.9× 319 3.9× 65 1.2× 39 0.9× 11 465
Cosimo Palmisano Italy 5 240 1.0× 92 1.0× 77 1.0× 21 0.4× 40 0.9× 5 282
P. Dolan United States 3 350 1.5× 118 1.3× 214 2.6× 50 0.9× 16 0.4× 3 446

Countries citing papers authored by Inay Ha

Since Specialization
Citations

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

Fields of papers citing papers by Inay Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Inay Ha. 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 Inay Ha. The network helps show where Inay Ha may publish in the future.

Co-authorship network of co-authors of Inay Ha

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

All Works

15 of 15 papers shown
1.
Jo, Geun‐Sik, et al.. (2014). A unified framework for augmented reality and knowledge-based systems in maintaining aircraft. National Conference on Artificial Intelligence. 2990–2997. 19 indexed citations
2.
Ha, Inay, et al.. (2014). Alleviating the cold-start problem by incorporating movies facebook pages. Cluster Computing. 18(1). 187–197. 23 indexed citations
3.
Jo, Geun‐Sik, et al.. (2014). A Unified Framework for Augmented Reality and Knowledge-Based Systems in Maintaining Aircra. Proceedings of the AAAI Conference on Artificial Intelligence. 28(2). 2990–2997. 8 indexed citations
4.
Ha, Inay, et al.. (2013). Link Strength-Based Collaborative Filtering for Enhancing Prediction Accuracy. 4. 1–4. 1 indexed citations
5.
Ha, Inay, et al.. (2013). Clustering Method based on Genre Interest for Cold-Start Problem in Movie Recommendation. Journal of Intelligence and Information Systems. 19(1). 57–77. 5 indexed citations
6.
Ha, Inay, et al.. (2013). Personalized advertisement system using social relationship based user modeling. Multimedia Tools and Applications. 74(20). 8801–8819. 12 indexed citations
7.
Ha, Inay, et al.. (2012). Collaborative Filtering based on Clustering method using Genre and Interest in SNS. 106–111. 1 indexed citations
8.
Ha, Inay, et al.. (2012). Collaborative Filtering Method based on User’s Behavior in Social Network. 101–105. 1 indexed citations
9.
Ha, Inay, et al.. (2011). Ontology-Driven Visualization System for Semantic Search. 6323. 1–6.
10.
Ha, Inay, et al.. (2011). Ontology-driven visualization system for semantic searching. Multimedia Tools and Applications. 71(2). 947–965. 4 indexed citations
11.
Kim, Heung-Nam, et al.. (2011). Collaborative user modeling for enhanced content filtering in recommender systems. Decision Support Systems. 51(4). 772–781. 50 indexed citations
12.
Ha, Inay, et al.. (2009). Collaborative Recommendation of Online Video Lectures in e-Learning System. Journal of the Korea Society of Computer and Information. 14(9). 85–94.
13.
Kim, Heung-Nam, et al.. (2009). Collaborative filtering based on collaborative tagging for enhancing the quality of recommendation. Electronic Commerce Research and Applications. 9(1). 73–83. 170 indexed citations
14.
Ha, Inay, et al.. (2008). Discovering Association Rules using Item Clustering on Frequent Pattern Network. Journal of Intelligence and Information Systems. 14(1). 1–17.
15.
Ha, Inay, et al.. (2008). Semantic Analysis of User Behaviors for Detecting Spam Mail. 91–95. 5 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.

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