Mi-Yen Yeh

967 total citations
45 papers, 597 citations indexed

About

Mi-Yen Yeh is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Mi-Yen Yeh has authored 45 papers receiving a total of 597 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Statistical and Nonlinear Physics, 15 papers in Artificial Intelligence and 14 papers in Computer Networks and Communications. Recurrent topics in Mi-Yen Yeh's work include Complex Network Analysis Techniques (18 papers), Opinion Dynamics and Social Influence (11 papers) and Data Management and Algorithms (10 papers). Mi-Yen Yeh is often cited by papers focused on Complex Network Analysis Techniques (18 papers), Opinion Dynamics and Social Influence (11 papers) and Data Management and Algorithms (10 papers). Mi-Yen Yeh collaborates with scholars based in Taiwan, United States and Canada. Mi-Yen Yeh's co-authors include Ming-Syan Chen⋆, Bi-Ru Dai, Shou-De Lin, Jen-Wei Huang, Cheng–Te Li, Philip S. Yu, Kun‐Lung Wu, Tei‐Wei Kuo, Yu-Ching Hsu and Junli Lu and has published in prestigious journals such as Information Sciences, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Computers.

In The Last Decade

Mi-Yen Yeh

45 papers receiving 570 citations

Peers

Mi-Yen Yeh
Jieying She Hong Kong
Mimmo Parente Italy
Saravanan Thirumuruganathan United States
Meng Qu United States
Amitabha Bagchi India
Yudian Zheng China
Sujith Ravi United States
Shenglin Zhao China
Lan Nie United States
Jieying She Hong Kong
Mi-Yen Yeh
Citations per year, relative to Mi-Yen Yeh Mi-Yen Yeh (= 1×) peers Jieying She

Countries citing papers authored by Mi-Yen Yeh

Since Specialization
Citations

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

Fields of papers citing papers by Mi-Yen Yeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mi-Yen Yeh. 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 Mi-Yen Yeh. The network helps show where Mi-Yen Yeh may publish in the future.

Co-authorship network of co-authors of Mi-Yen Yeh

This figure shows the co-authorship network connecting the top 25 collaborators of Mi-Yen Yeh. A scholar is included among the top collaborators of Mi-Yen Yeh 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 Mi-Yen Yeh. Mi-Yen Yeh 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
1.
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Liu, Vincent, et al.. (2020). Attribute-Aware Recommender System Based on Collaborative Filtering: Survey and Classification. Frontiers in Big Data. 2. 49–49. 20 indexed citations
3.
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Li, Cheng–Te, et al.. (2019). MARINE: Multi-relational Network Embeddings with Relational Proximity and Node Attributes. 470–479. 22 indexed citations
5.
Yeh, Mi-Yen, et al.. (2018). Deep Censored Learning of the Winning Price in the Real Time Bidding. 2526–2535. 20 indexed citations
6.
Yeh, Mi-Yen, et al.. (2018). Worship prediction: identify followers in celebrity-dived networks. World Wide Web. 22(1). 347–373. 1 indexed citations
7.
Yeh, Mi-Yen, et al.. (2017). Preserving Proximity and Global Ranking for Node Embedding. Neural Information Processing Systems. 5168–5177. 4 indexed citations
8.
Yeh, Mi-Yen, et al.. (2017). PRUNE: Preserving Proximity and Global Ranking for Network Embedding. Neural Information Processing Systems. 30. 5257–5266. 31 indexed citations
9.
Yeh, Mi-Yen, et al.. (2017). Node reactivation model to intensify influence on network targets. Knowledge and Information Systems. 54(3). 567–590. 2 indexed citations
10.
Yeh, Mi-Yen, et al.. (2016). Predicting popularity of articles on bulletin board system. 3. 169–176. 2 indexed citations
11.
Yeh, Mi-Yen, et al.. (2015). Bandwidth-efficient distributed k-nearest-neighbor search with dynamic time warping. 551–560. 3 indexed citations
12.
Yeh, Mi-Yen, et al.. (2013). Profiling Moving Objects by Dividing and Clustering Trajectories Spatiotemporally. IEEE Transactions on Knowledge and Data Engineering. 25(11). 2615–2628. 9 indexed citations
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Yeh, Mi-Yen, et al.. (2013). Endurance-Aware Flash-Cache Management for Storage Servers. IEEE Transactions on Computers. 63(10). 2416–2430. 9 indexed citations
15.
Wei, Ling-Yin, et al.. (2013). Discovering Point-of-Interest Signatures Based on Group Features from Geo-social Networking Data. 2. 182–187. 2 indexed citations
16.
Yeh, Mi-Yen, et al.. (2013). MLC-flash-friendly logging and recovery for databases. 1541–1546. 2 indexed citations
17.
Yeh, Mi-Yen, et al.. (2012). Random Error Reduction in Similarity Search on Time Series: A Statistical Approach. 858–869. 5 indexed citations
18.
Yeh, Mi-Yen, et al.. (2011). A flash-friendly B<sup>&#x002B;</sup>-tree with endurance-awareness. 29–36. 3 indexed citations
19.
Yeh, Mi-Yen, Kun‐Lung Wu, Philip S. Yu, & Ming-Syan Chen⋆. (2008). LeeWave. Proceedings of the VLDB Endowment. 1(1). 586–597. 7 indexed citations
20.
Dai, Bi-Ru, Jen-Wei Huang, Mi-Yen Yeh, & Ming-Syan Chen⋆. (2006). Adaptive Clustering for Multiple Evolving Streams. IEEE Transactions on Knowledge and Data Engineering. 18(9). 1166–1180. 63 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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