Tak-chung Fu

2.0k total citations · 1 hit paper
21 papers, 1.3k citations indexed

About

Tak-chung Fu is a scholar working on Signal Processing, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Tak-chung Fu has authored 21 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Signal Processing, 9 papers in Management Science and Operations Research and 8 papers in Artificial Intelligence. Recurrent topics in Tak-chung Fu's work include Time Series Analysis and Forecasting (16 papers), Stock Market Forecasting Methods (8 papers) and Complex Systems and Time Series Analysis (6 papers). Tak-chung Fu is often cited by papers focused on Time Series Analysis and Forecasting (16 papers), Stock Market Forecasting Methods (8 papers) and Complex Systems and Time Series Analysis (6 papers). Tak-chung Fu collaborates with scholars based in Hong Kong and China. Tak-chung Fu's co-authors include Fu-Lai Chung, Robert W. P. Luk and Vincent Ng and has published in prestigious journals such as Computers & Mathematics with Applications, Engineering Applications of Artificial Intelligence and PolyU Institutional Research Archive (Hong Kong Polytechnic University).

In The Last Decade

Tak-chung Fu

21 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review on time series data mining

2010 968 citations Tak-chung Fu Engineering Applications of Artificial Intelligence profile →

Peers

Tak-chung Fu

SP

AI

EE

MSOR

CVPR

Thanawin Rakthanmanon United States

Eugene Tuv United States

Jesin Zakaria United States

Bhogeswar Borah India

Hesam Izakian Canada

Patrick P. K. Chan China

S. Chu United States

Nikolay Laptev United States

Tim Januschowski United States

Jan Gasthaus United States

Thanawin Rakthanmanon United States

Tak-chung Fu

1.2k ×1.3

SP

879 ×1.5

AI

262 ×0.9

EE

73 ×0.3

MSOR

230 ×1.6

CVPR

Citations per year, relative to Tak-chung Fu Tak-chung Fu (= 1×) peers Thanawin Rakthanmanon

Countries citing papers authored by Tak-chung Fu

Since Specialization

Citations

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

Fields of papers citing papers by Tak-chung Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tak-chung Fu. 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 Tak-chung Fu. The network helps show where Tak-chung Fu may publish in the future.

Co-authorship network of co-authors of Tak-chung Fu

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

All Works

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20 of 20 papers shown

1.

Fu, Tak-chung, et al.. (2017). Improvement algorithms of perceptually important point identification for time series data mining. 1. 11–15. 12 indexed citations

2.

Fu, Tak-chung, et al.. (2013). Adopting genetic algorithms for technical analysis and portfolio management. Computers & Mathematics with Applications. 66(10). 1743–1757. 29 indexed citations

3.

Fu, Tak-chung, et al.. (2011). Models for portfolio management on enhancing periodic consideration and portfolio selection. 176–180. 1 indexed citations

4.

Fu, Tak-chung, et al.. (2008). Discovering the Correlation between Stock Time Series and Financial News. 880–883. 8 indexed citations

5.

Fu, Tak-chung, et al.. (2008). Stock time series visualization based on data point importance. Engineering Applications of Artificial Intelligence. 21(8). 1217–1232. 21 indexed citations

6.

Fu, Tak-chung, et al.. (2007). Representing financial time series based on data point importance. Engineering Applications of Artificial Intelligence. 21(2). 277–300. 63 indexed citations

7.

Fu, Tak-chung, et al.. (2007). Distributional Similarity Model for Multi-modality Clustering in Social Media. 1 indexed citations

8.

Fu, Tak-chung, et al.. (2007). Distributional Similarity Model for Multi-modality Clustering in Social Media. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 268–271. 3 indexed citations

9.

Fu, Tak-chung, et al.. (2007). Analysis and Visualization of Time Series Data from Consumer-Generated Media and News Archives. 259–262. 3 indexed citations

10.

Fu, Tak-chung, et al.. (2006). Mining of Stock Data: Intra- and Inter-Stock Pattern Associative Classification.. 30–36. 18 indexed citations

11.

Fu, Tak-chung, et al.. (2006). Financial Time Series Segmentation based on Specialized Binary Tree Representation.. 70(1). 3–9. 19 indexed citations

12.

Fu, Tak-chung, et al.. (2006). Stock time series pattern matching: Template-based vs. rule-based approaches. Engineering Applications of Artificial Intelligence. 20(3). 347–364. 78 indexed citations

13.

Fu, Tak-chung, et al.. (2006). SBT-QL: A Stock Time Series Query Language based on Specialized Binary Tree Representation. Advances in intelligent systems research. 4 indexed citations

14.

Fu, Tak-chung, et al.. (2005). Adaptive Data Delivery Framework for Financial Time Series Visualization. 2. 267–273. 3 indexed citations

15.

Fu, Tak-chung, et al.. (2005). Agent-Based Network Intrusion Detection System Using Data Mining Approaches. 1. 131–136. 16 indexed citations

16.

Fu, Tak-chung, et al.. (2005). SBT-Forest, an Indexing Approach for Specialized Binary Tree. 1. 149–154. 2 indexed citations

17.

Fu, Tak-chung, et al.. (2005). Incremental stock time series data delivery and visualization. 279–280. 4 indexed citations

18.

Fu, Tak-chung, et al.. (2004). Progressive time series visualization in a mobile environment. 662–667 Vol.2. 3 indexed citations

19.

Chung, Fu-Lai, Tak-chung Fu, Robert W. P. Luk, & Vincent Ng. (2003). Evolutionary time series segmentation for stock data mining. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 83–90. 34 indexed citations

20.

Fu, Tak-chung, Fu-Lai Chung, Vincent Ng, & Robert W. P. Luk. (2002). Evolutionary segmentation of financial time series into subsequences. 1. 426–430. 27 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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